The Hyelight Process, an Adaptive Difficulty System That Enhances Player Enjoyment During Gameplay

University of the Aegean, Syros Department of Product & Systems Design Engineering

Thesis Project The Hyelight process, An adaptive difficulty system that enhances player enjoyment during gameplay

Maximos Malevitis, October 2017

Committee Supervisor: Dr. Spryridon Vosinakis 1st Member: Dr. Panagiotis Koutsampasis 2nd Member: Dr. Panagiotis Kuriakoulakos

I declare responsibly that the thesis work is entirely a personal work and no part of it is copied from printed or online sources, nor translated from foreign language sources, nor it is a reproduction from other researchers’ or students’ work. Wherever I have been based on ideas or texts of others, I have tried, as far as possible, to clearly make a reference following the academic ethics

Δηλώνω υπεύθυνα ότι η διπλωματική εργασία είναι εξ’ ολοκλήρου δικό μου έργο και κανένα μέρος της δεν είναι αντιγραμμένο από έντυπες ή ηλεκτρονικές πηγές, μετάφραση από ξενόγλωσσες πηγές και αναπαραγωγή από εργασίες άλλων ερευνητών ή φοιτητών. Όπου έχω βασιστεί σε ιδέες ή κείμενα άλλων, έχω προσπαθήσει, όσο είναι δυνατόν, να το προσδιορίσω σαφώς μέσα από την χρήση αναφορών, ακολουθώντας την ακαδημαϊκή δεοντολογία.

M.M.

Dedicated to my parents, the strongest people alive. Without your help none of this would have ever been possible.

Special thanks

I would like to sincerely thank my friend Nikos Nikolaou, the coding mastermind behind the game I created, for without his help the game would not have been nearly as interesting and interactive!

I would also like to thank Nikos Kolliniatis, a dear friend whose sketches and music always have and always will inspire me to create!

I want to thank Stella Vaka, the person who stood by my side through thick and thin, always pushing me to do my best and reach my potential. Your never-ending support guided me through the darkness.

Finally, I would like to thank the three greatest educators I could ask for.

Dr. Spyros Vosinakis, for guiding me from the first moment I mentioned I wanted to become a game designer. You showed me the proper academic procedure and thus the way to improve my research substantially.

Dr. Panagiotis Koutsampasis, for teaching me the importance of User Experience and usability testing, the pillar of my thesis. You helped me realize what I want to research and improve in the field of games design, player experience and game feel.

Dr. Panagiotis Kuriakoulakos, for opening new doors for me in more than a couple departments of creativity. You helped me follow my dream and urged me to reach my potential before even I have decided what I wanted to do.

TABLE OF CONTENTS

1 Introduction ...... 11 1.1 Problem Statement ...... 11 1.2 Aim of the Thesis ...... 11 1.3 Methodology ...... 12 2 Games and Difficulty ...... 13 2.1 Why difficulty is a crucial part of games ...... 13 2.2 Difficulty Curve ...... 13 2.3 Difficulty vs Challenge and Difficult vs Punishing ...... 15 2.4 Common Difficulty Systems ...... 19 2.4.1 Difficulty Levels ...... 19 2.4.2 Dynamic Difficulty Adjustment ...... 22 2.5 On the matter of Dominant Strategies ...... 26 3 The Player ...... 27 3.1 User modelling ...... 27 3.2 Player Modelling ...... 28 3.2.1 Play Personas ...... 28 3.2.2 Dynamic Player Modelling ...... 30 4 The case for games with Multiple Gameplay Elements ...... 31 4.1 What are “multiple gameplay elements” ...... 31 4.2 Games that make use of multiple gameplay elements ...... 32 4.3 A brief introduction to Flow Theory ...... 37 4.3.1 Games want to keep players in the Flow Channel ...... 40 5 The Hyelight System ...... 42 5.1 System Fundamentals ...... 42 5.1.1 Player Profiling ...... 42 5.2 Targeted Dynamic Difficulty Adjustment ...... 48 5.2.1 Area Clustering ...... 48 5.2.2 Difficulty Curve ...... 49 5.2.3 Adaptation ...... 50 5.3 Hypotheses on the Player Experience ...... 51 5.4 Hyelight Concept Model ...... 52 6 Testbed, Hyelight ...... 53 6.1 Story ...... 53 6.2 Design ...... 53

6.2.1 Concept art ...... 53 6.2.2 Art Style and early experimentation ...... 54 6.2.3 Main Character and Final Art- Style ...... 57 6.2.4 Animation ...... 58 6.2.5 Enemies ...... 59 6.2.6 The World ...... 61 6.2.7 Visual Effects...... 64 6.3 Gameplay ...... 66 6.3.1 Platforming ...... 66 6.3.2 Combat ...... 66 6.3.3 Bullet Hell elements ...... 68 6.3.4 Data collection and profile analysis ...... 70 6.3.5 Area Clusters ...... 71 6.3.6 Fractal Curves ...... 71 6.3.7 Difficulty manager ...... 72 7 System Evaluation ...... 73 7.1 First System test- Dishonored 2 ...... 73 7.1.1 Gameplay ...... 73 7.1.2 Level division and Area Clusters ...... 74 7.1.3 Difficulty Curves ...... 75 7.1.4 System Evaluation Process ...... 76 7.1.5 Player Approach and Reward System ...... 76 7.2 Second System test – Pen and Paper games ...... 77 7.2.1 Pen and Paper Games ...... 77 7.2.2 Evaluation Participants ...... 78 7.2.3 Evaluation Process ...... 78 7.2.4 Evaluation results ...... 80 7.3 Final System Test – Hyelight Game ...... 81 7.3.1 Phase 1 - Pregame interview ...... 81 7.3.2 Phase 2 - Controls tutorial ...... 82 7.3.3 Phase 3 – Manual difficulty playthrough ...... 83 7.3.4 Phase 4 – Targeted dynamic difficulty Adjustment Playthrough ...... 83 7.3.5 Phase 5 - Final Interview...... 84 7.3.6 The role of the researcher ...... 86 7.3.7 Results and analysis ...... 87 7.4 System Design Conclusions ...... 87

8 Final thoughts ...... 89 8.1 Conclusions ...... 89 8.2 Future Research ...... 90 9 Appendix ...... 91 9.1 Individual Tester Results...... 91 9.2 Difficulty calculation algorithm ...... 101 9.3 Game Stills ...... 107 10 References ...... 110

1 INTRODUCTION

The importance of this thesis

With games being increasingly accessible to all and in prices that most gamers can afford to get at least 4-5 games per month (not counting free games), game design is tending to create titles that are easier to beat in a short amount of time. The amount of gameplay depth in games is ever increasing, with titles like NieR Automata and Dishonored from the single player genre as well as Overwatch in the multiplayer genre, containing an abundance of different game mechanics to accommodate all player types (Arkane, 2013) (Platinum Games, 2017) (Overwatch, 2016). The massive success of the aforementioned titles is a good basis from which we can safely assume that the multiple gameplay element will grow in the future. The project analyzed in this thesis suggests a way to keep player interest in a specific game high for a longer amount of time. A game that plays in the way each individual values most, can keep engagement levels high. After the game’s completion, since the gameplay can vary greatly between playthroughs, re-playability is greatly boosted, since with slight differences in player choice, the game can be engaging in a whole new way. An advantage of the proposed workflow is that it harnesses already implemented systems and gameplay styles to improve

1.1 PROBLEM STATEMENT

We want to devise a method which produces a balanced difficulty curve, where player skill is judged in specific areas rather as a whole and the game can adapt its difficulty accordingly. The most important recent non-multiplayer games rely heavily on Difficulty Meters to adjust their difficulty on the fly (Arkane, 2013) (Bethesda, 2011) (CD Project Red, 2007- 2014) (Platinum Games, 2017), whereas Dynamic Difficulty Adjustment Systems evaluate player skill as a whole instead of judging different areas of expertise and adapt accordingly. Overall adaptability of difficulty can cause a plethora of unforeseen problems on player enjoyment (Adams, 2008). Player centered design methods will be used to create and test the suggested method on a prototype.

1.2 AIM OF THE THESIS The aim of this thesis is through scientific process, to analyse current difficulty systems and create a new tool that can aid game designers in the difficulty management process. The tool to be created will be an adaptive difficulty system that can be implemented in games that contain multiple gameplay elements. A game with multiple gameplay elements is in this context defined as a game that offers players more than a single way to interact with and progress through the game world.

The new difficulty adjustment system is created as a player-cantered approach to difficulty in games. Through play the game should adapt to create a tailored experience to every individual player. With the implementation of the aforementioned system, players will stay in the flow zone for prolonged periods of time.

1.3 METHODOLOGY To successfully complete the aim of the thesis, the following methodology will be followed. A thorough analysis of games and difficulty will be presented. This analysis will include the various methods of balancing a game’s difficulty, containing -but not exclusively- the terms of difficulty levels, dynamic difficulty adjustment systems and the difficulty curve design tools. Both the benefits and the drawbacks of these methods will be presented as studied in both research papers and discussed by game designers. Based on the results of the analysis, a new difficulty system will be developed. The proposed system will be an adaptable difficulty system that can be implemented in games with multiple gameplay elements. An example of parameters that can be used to provide results in certain types of playstyles will also be included. Afterwards, a game with multiple gameplay elements will be developed from scratch, using the preceding adaptability system. Once ready, the prototype will be presented to player groups of the target audience and tested. The tests will mainly include whether the tool created supports the hypotheses made previously. Player experience will be evaluated with a focus in the time each player journeys through the flow channel. Finally, the results of the evaluation will be presented to support or disprove the tool’s success.

2 GAMES AND DIFFICULTY

“A game is a problem-solving activity, approached with a playful attitude” -Jesse Schell

Games are indeed problem- solving activities and should be approached as such. The inherit interest of games lies within constant problems being presented to the players along with a set amount of resources and a solution asked from them. Players relish in this process of giving solutions to any challenge the game puts at their feet.

The second part of Schell’s quote describes the attitude with which games should be approached in order for them to be considered as such. We face problem solving in our everyday lives in many different forms. Figuring out what the best insurance company suits your needs, or deciding on the best marketing plan for your company are two examples of everyday problem solving that under no circumstances are considered as “games”. The previous examples cannot be categorized as games solely because they cannot be approached in a playful manner.

2.1 WHY DIFFICULTY IS A CRUCIAL PART OF GAMES

In order for games to be engaging, a degree of difficulty is always important to be kept. Since games are problem-solving activities, through a game’s difficulty, a player is provided with a qualitative method of measuring his skill. If there is no fluctuation of a game’s difficulty, the experience becomes stale and unengaging as the player’s skill increases through practice. In order to avoid creating unengaging experiences, game designers make the difficulty of their products increase with time so as to compensate for the increase in player skill. (Schell, 2015)

A reliable method to increase the difficulty of the game is the Difficulty Curve.

2.2 DIFFICULTY CURVE

A Difficulty Curve is essentially a two- dimensional graph consisting of a Difficulty axis and a Progression axis. A relatively low difficulty exists throughout the early stages of the game, in order for players to be acquainted with the controls and the mechanics. This part of the graph is called the “Learning Curve”, during the learning curve, the main focus of the design is for the players to learn the core game’s mechanics. Players need to learn how to utilize each mechanic in a useful manner to aid their journey in the gameworld. The part of the learning curve is completed once the player can make strategic decisions with the tools the game has provided

13 him so far. Knowledge of multiple mechanics at this point is not mandatory, the main gameplay styles are roughly introduced and their primary usage is taught in a repetitive manner, so that players of all skill ranges adapt to it.

In the case of a platforming game such as Mario, the player is introduced to the game world and its many mechanics. The game doesn’t start with a huge jump over a gap, on the contrary, it gives the player some space to walk back and forth. The second task asked of the player is to break a box by jumping, breaking boxes is the main source of income and points in the game. The third actions that is requested from the player is to jump over a tube, a safe jump that has no chances of failure, afterwards the first gap is introduced and the player can now face death for the first time. Only after all the other steps are asked from the player, only then are enemies spawned, since to kill them, a more precise jump is required.

After this initial learning curve, difficulty ramps up, presenting a hill-valley behavior with almost every hill higher than the last. The rise in difficulty is almost constant, through game progress, it always rises, even if only by a little. This is due to the fact that player skill is increased through play. The aforementioned concept stems from flow theory, where the rate of increase in difficulty is suggested to follow the rate of increase in player skill. In the most widely used difficulty curves, right after local peaks, a small drop in difficulty occurs. This design aims for a place where players can relax after a stressful encounter and have time to understand the mechanics they used (Razavi, 2017).

For example, after every major fight in the Dark Souls Series, since every encounter is very stressful and demanding of the player, there lies a resting area. That area is not only empty of enemies or traps, it is also a place where players cannot invade you and you can relax or even take a break from the game. The last might not seem important, but in Dark Souls, there is no “pause” function, so places that are safe from both enemies and other invading players are safe havens where players can relax freely.

The rest of the game’s difficulty curve can be broken down to numerous smaller tense and release cycles of play, similar to the one described above. The combination of all these smaller, fractal curves, produce the final game.

Usually the last part of the experience has a significant rise in difficulty in order for the last encounters to be the most exciting, thus leaving the player with a feeling of accomplishment. The reason that the last part is considerably more difficult is that

14 even if it takes longer for the player to complete that portion, he gets a boost in interest when he completes the game. An easier last encounter makes for more forgettable experiences. Similar to movies, there is a need for a “Grand Finale” where the gameplay can conclude along with the story.

Difficulty is a relative term and every player creates their own experience with each game they play. What may be difficult for some, can be simple for others. The following part will cover the differences of difficulty and challenge.

2.3 DIFFICULTY VS CHALLENGE AND DIFFICULT VS PUNISHING

In this thesis, there is mention of both difficulty and challenge, however, they are different terms. A game has a difficulty level, so difficulty is a way of communicating how hard the game is overall compared to the average player (with the average player being the one the game was designed for). Difficulty is a metric in games, it is a way for game designers as well as reviewers to compare games to each other. It has to do with number of tries required to complete a level, or the amount of artificial difficulty inherent in it.

Artificial difficulty is defined as: “A term to describe games that have enemies that are too powerful to be killed even through intelligent gameplay and the player must resort to cheap tactics and exploits because the enemy cannot be killed in a straight up fight due their health and damage surpassing the player's. The difference between artificial difficulty and real difficulty is that real difficulty can be overcome through intelligent gameplay such as planning out how you will attack a group so you will not take any damage, being patient, and being cautious. Real difficulty is achieved through enemies that have intelligent abilities that the player must learn and learn to avoid while artificial difficulty is achieved simply by raising the enemies' damage and health.” (Urban Dictionary, n.d.)

Cat Mario, a game full of artificial difficulty

In short, artificial difficulty gives no cues for enemy presence or patterns and requires more of the trial and error approach to be beat. A great example of a game with artificial difficulty is cat-Mario. A Super Mario clone, where anything can kill you without any form of telegraphing. To beat the game, you need to die repeatedly, usually over a couple hundred times per level. It is a very frustrating game created for those who enjoy unfair playthroughs that require multiple tries to beat.

Challenge on the other hand is a reference to personal experience instead of overall design. Players are challenged through play, and even though a game of medium overall difficulty can be easy for some, it can also be impossible to beat for others. When we refer to challenge from now on, we refer to each individual experience in the game world, instead of the game’s difficulty. The main part of the thesis’s proposed system is to perceive and improve challenge through difficulty, to tailor the challenge level to the individual and to create a stable difficulty in a game. If players enjoy individually tailored experiences, the game’s difficulty will be the same for everyone and can be judged more coherently.

As it was proven through the massive success of the Dark Souls series, players still crave impossibly difficult games. They enjoy the challenge and are thrilled even in the through of a game that asks their maximum performance to advance further.

But, if players enjoy difficult games such as these, why is the design trend to make games less challenging for them? The answer lies in the numerous failures of the first PC games. The first game designers that worked for the game industry were the ones that programmed the arcade games of 1970’s and 1980’s. In the old arcades, players bought “lives” in the public machine and got the chance to play for a while. The reasoning behind their invention was monetization through many playthroughs. Every time the player lost, she would pay more to keep on playing. The difficulty of those games was very high, because having a good player be able to play for more than ten minutes with a single coin would not be profitable in the long run. So, designers made games hard enough, that they would require many tries to beat. Those same designers, transitioned to the console games industry which made its debut around that time and designed for games for the likes of the famous Atari 2600, one of the most successful second generation of home consoles in 1976.

Back then, the “personas” used to create games were very limited. It could be summed up to “Male, 8 – 14 years old, will not be buying games regularly”. For this exact persona model, games like the ones of the old arcades were very successful, since they required many hours of play to complete and would still feel challenging. The success of games like these was short-lived however, since after a while, when the player base was increased and grew up, they could afford to buy games for themselves, so replay-ability became less of an issue. Production costs for games skyrocketed and game designers sought for an even greater audience. The newly introduced players did not have the mentality of difficult games and so in order to keep the market growing, designers started lowering their products’ difficulty.

Games like the old Atari games were punishing games, not difficult ones. Punishing games incorporate large content that has artificial difficulty and unforgiving mechanisms. A punishing game, is a game where the amount of telegraphing is reduced to a minimum and most challenges require memorization. Telegraphing is the process where before something happens that can be dangerous for the player, the game presents him with a warning. Telegraphing can be present in many ways, from the aesthetic component of the game down to the core mechanics level.

A good example of this lies in Dark Souls 1, when the player manages to pass a difficult part of a medieval castle, he finds himself looking at a burned bridge full of burned-down bodies. If the player remembers that he saw a large dragon earlier on, he can hide to avoid the devastating flames the dragon will rain upon the area after a while. Another example is the way Boss-monsters perform their most powerful attacks in the Massive Multiplayer Role-Playing Game, Tera. Bosses have an abundance of visual or sound cues before attacking with their most powerful attacks, from visual effects to the ground shaking. This way, the contestants can all be prepared for the stage that follows.

In punishing games on the other hand, there is no telegraphing, that means that enemies will kill you in a way that feels “unfair”. This unfair feeling can by itself discourage players from playing the game, and can lead them to search for new ones.

For a game to be difficult, yet fun, there are a number of guidelines that can be followed. To start off, there has to be a limited number of Artificial Difficulty encounters in the game, and if they exist, they have to be there to improve the narrative of the game. There has to be telegraphing, so that players don’t feel like the game is being unfair. There needs to be consistency of rules, everything you find

17 in the game should adhere to the same ruleset. When the world is designed like this, players feel more immersed and less threatened by unexpected “unfair” encounters. The spawn points of the player in games that require trial and error, have to be fairly close to each other to avoid long re-traversal times with no real gameplay value. Lastly, the players should have enough tools to progress through the game. Limiting the player’s toolset to a single strategic choice can be quite tedious (Portnow, When Difficult Is Fun - Challenging vs. Punishing Games - Extra Credits, 2013).

In conclusion, a game can be extremely difficult and yet enjoyable and successful, if it follows the guidelines above. Punishing games on the other hand, are a genre that no longer works with the industry- player base combination we now have.

2.4 COMMON DIFFICULTY SYSTEMS

As we have already mentioned, keeping the players in the flow zone throughout the whole experience is essential in order for it to have maximum impact. There are numerous difficulty systems that are used by game designers, all with their strong and weak points. In the following section, the most commonly used difficulty systems are presented alongside their strengths and weaknesses. To start off, many games strive to keep players in flow by providing a choice among different difficulty levels.

2.4.1 Difficulty Levels

Difficulty Levels are essentially different versions of the games’ encounters. Changing the overall difficulty of the game through this option is a way that lets players tailor the game to their own needs. Difficulty Levels are predetermined and designed by the game development team.

Usually the Difficulty Levels of games have three choices: Easy, Medium and Hard. Sometimes the choices are more, consisting of extra hard modes such as “Nightmare, Hell or 1999 mode” the latter one consisting of unfair challenges and intended to offer replay value to the game rather than being an available difficulty level during the first playthrough.

Depending on the game, different aspects of gameplay become more difficult. There are three main ways the game can change using the Difficulty Levels. The first one is by strengthening the player’s adversaries (making the enemies shoot more accurately in an FPS, for example), the second is by limiting the player’s abilities (reducing player health or armor) and the last is by changing the environment (decreasing the length of a platform the player will need to balance on in a platform game, or decreasing the amount of health kits available in an FPS). Difficulty Levels change gameplay using any combination of the aforementioned ways. Standard Difficulty Levels change the challenge in a set, predesigned way over which the player has no control.

Several problems emerge through the use of Difficulty Levels, many of them thoroughly debated among game designers. Problems with difficulty levels

Difficulty levels are widely used, but still not the perfect solution to game difficulty. Bellow, the most important problems with difficulty levels are highlighted in order to be understood for future research. The following evidence is based on the works of James Portnow (Portnow, Extra Credits, n.d.) and Andrew Glassner (Glassner, 2004). 1. Player is prompted to choose too early on Games usually ask the player to choose a difficulty level right at the beginning, and at that point the player doesn't actually know how hard the game is going to be because he hasn't played it yet (Glassner, 2004).

2. Options are too coarse What if medium mode is too easy, but hard mode is too hard? The categories are too widely spaced. The choice between three or five Difficulty Levels can be very limiting to players who want a more tailored experience (Glassner, 2004)

3. Options are too broad Which means that the difficulty settings apply generally across all the different types of challenges in a game, and a player might be good at one kind, such as shooting, but not at another such as driving. Which setting should he choose? (Adams, 2008)

4. They are too persistent I.e. a difficulty setting doesn't adjust to the player's rate of improving skill, especially if he's not allowed to change the setting later. The difficulty growth curve, at whatever setting, may prove to be too steep or too shallow for the player (Adams, 2008).

5. They are too general Glassner points out that many games introduce new player-actions as play goes on, which require new skills. The player may be better at some of them than at others. Because the player doesn't know what skills he will be asked to learn, he may regret his choice of difficulty level when a new action is introduced (Glassner, 2004).

6. Inability of players to intuitively understand which setting will prove the most enjoyable With this statement, James Portnow describes the fact that when choosing a difficulty from a menu, players cannot understand the future difficulty curve of the game. This leads to many players missing out on more interesting or appropriate game experiences for each of them (Portnow, The True Genius of Dark Souls II - How to Approach Game Difficulty, 2014).

7. Predetermined psychological factors Many players tend to choose based on social bias, refusing to play on “Easy” since they feel this mode is for “bad” players. Others steer away from “Hard” modes, at times fearing they might not be good enough, and other times feeling like they cannot afford time to beating the game but want to see the story. Choosing a difficulty level like this leads to players getting a sup- optimal experience (Portnow, The True Genius of Dark Souls II - How to Approach Game Difficulty, 2014).

8. The “true” game conundrum Many players argue over which Difficulty setting is the “true” game. They believe games should be played on a certain difficulty to retain their original design, since the lower settings are considered as a compromise. This leads to many players choosing their Difficulty Level by disregarding their own capabilities (Portnow, The True Genius of Dark Souls II - How to Approach Game Difficulty, 2014).

9. Inability of casual players to judge their skill As proven by Justin Kruger and David Dunning of Cornell University (Dunning, 1999), humans without experience in certain fields can exhibit inflated self- assessment. Unskilled players are proven to overestimate their abilities and chose inappropriate Difficulty Levels when prompted. In contrast to this, more experienced players tend to underestimate themselves and their gameplaying ability (Justin T. Alexander, 2013).

2.4.2 Dynamic Difficulty Adjustment

Another well- known way of approaching a game’s difficulty is by using Dynamic Difficulty Adjustment (referred to as DDA from now on) Systems - sometimes also called Dynamic Difficulty Balancing. It is the process of automatically changing parameters, scenarios, and behaviors in a video game in real-time, based on the player's ability, in order to avoid making the player bored (if the game is too easy) or frustrated (if it is too hard). The preceding statement sounds very similar to flow theory by (Csikszentmihalyi M. , 2000) That means that an ideal DDA system keeps the player in flow regardless of skill level, since such a system is keeping every player inside his personal flow-zone.

DDA systems have been implemented in games as early as 1981 with Intellivision’s game Astrosmash. Astrosmash became harder as the game progressed but when the player was running out of lives, it got easier again for a short period of time. Its system made it very popular among both casual and experienced gamers, since they could all play for a prolonged amount of time. Every playthrough costed coins, so the DDA system inside it made sure that players played for roughly the same amount of time, but rewarded better players with higher scores since the difficulty they played at was harder (Mattel, 1981).

What DDA systems do, can be broken down in two parts: First, they monitor a player’s overall performance. This monitoring includes but is not limited to: hit percentage, health lost per fight, number of deaths in a specific jumping puzzle or boss and time of completion of each level. Through monitoring the player performance, the system can make educated decisions on many different aspects of the game. The system can predict how long the gameplay experience will last for the current player by dividing the amount of the total

Secondly, the DDA systems adjust the game’s difficulty to reflect the player’s progress. If the game’s parameters judge that the player is over-performing in the current context, the game will get harder, if the player is judged to be underperforming, the game will get easier.

Typical Dynamic Difficulty System Adjustment

There are several ways the game gets harder or easier. These can be divided in two broad categories, Player Adjustment and World Adjustment.

Player Adjustment: In this case, the game’s difficulty changes by altering the players abilities such as health, damage inflicted or giving the player the ability to skip a specific part of the game. The game can also provide loot that can aid the player, such as more powerful weapons or abilities. The Sin Episodes series of games is famous for the dynamic difficulty system it implemented that could aid the player during gameplay (Harward, 2007).

A more detailed DDA system

World Adjustment: In this case, enemy health, frequency of powerups available to the player, enemy accuracy and speed or even jumping puzzle distances are fluctuating in order to either pose a bigger obstacle to the player or provide some help.

Even though DDA systems were designed to help maintain players in a constant state of flow, they can sometimes have the exact opposite effect. Bellow, the most significant drawbacks of DDA technology are presented, based on the works of James Portnow (Portnow, Extra Credits, n.d.) and Adam Ernest (Adams, 2008).

Problems with Dynamic Difficulty Adjustment Systems

1. Some players hate it As Adam Ernest mentions in his column, DDA systems don’t always have the warmest of receptions from players, especially when they cannot be switched of. The main reason behind it is that it makes them feel patronized when they discover that the game is going easy on them when they are not good enough, feeling the need to get better and win regardless of the number of tries required.

2. Players can exploit them It used to be common practice in DDA systems (Schell, 2015) reported by both designers and players. When the player discovers that a DDA system is used, they can decide to lose repeatedly before a hard boss-fight or a hard area, and then when they fight the actual battle, it’s much easier.

3. DDA doesn’t work for all kinds of challenges While adjusting an opponent’s health pool or aim can be quite easy, many other parts of games are not so easy to adapt. These include puzzles, which are designed with a specific difficulty and recreating a different puzzle for every ability level and game instance can be expensive and tedious work for the design team.

4. DDA can create absurdities In some racing games, if you crash your car, the game slows down the other cars to give you an opportunity to catch up. There is also the notorious rubber-band effect, where cars in the front run slower than cars in the back, so as to give the option for cars in the last places to catch up to the front line once more. For casual games this can be acceptable, but not for serious racing simulators. “A DDA mechanism must operate in a way that is logically and emotionally consistent with the game world” says Ernest Adams.

5. DDA ruins pacing and obviates good level design A hypothetically perfect DDA system that always kept all challenges at the same level of perceived difficulty would ruin the pacing of the game. It would be like listening to a Beethoven symphony in which every note is played at exactly the same volume, or walking around an art museum wearing colored sunglasses. A well-designed level, with its varying emotional tones, is a work of art in its own right, and it deserves to be appreciated as such.

6. It spoils the reality of the world According to Jesse Schell*, DDA systems can potentially spoil the reality of the game world. Players need to feel that the world is real and consistent, something hard to do when the opponent’s abilities are not absolute, but based on player skill.

7. Players Improve with practice Sometimes, players don’t want the game to adapt to their skill level, but on the contrary, they want to get better and defeat the difficult parts by training more. Thus, making the game easier for them can lead to players feeling insulted or disappointed (as was the case with “The Incredible Hulk” game for PS2).

8. DDA shouldn’t be hidden Hidden DDA systems make players feel cheated if they complete the game without knowing the system has been implemented. The value of the success in game completion is lessened when players realize the game was getting easier instead of them getting better.

9. DDA Systems do not follow a difficulty curve When gameplay difficulty changes constantly, there is no specific difficulty curve involved. This keeps the player in a constant pressure with small breaks where the game naturally gives “breathing room”. What if the player reaches those more relaxing parts of the game right after a relatively low tense cycle?

2.5 ON THE MATTER OF DOMINANT STRATEGIES

The main difference between games and puzzles is that puzzles have a dominant strategy (Schell, 2015). A dominant strategy is defined as regardless of what any other players do, the strategy earns a player a larger payoff than any other. Hence, a strategy is dominant if it is always better than any other strategy, for any profile of other players' actions. (Shor, 2017)

The problem with dominant strategies in games is that they strip the game of its replay value once discovered. Since the best solution is always the same, the players cease to be entertained. That lack of entertainment is due to loss of challenge after the initial playthrough, and the main reason puzzles are not as interesting to resolve once solved.

So, keeping a game fresh by presenting more ways to play, always keeping a balance between them is a valid ticket out of the dominant strategy swamp of mediocre replay-ability. This argument naturally leads us to the next topic.

3 THE PLAYER

The need to categorize the target audience is not new to the design process. When a product is to be produced for the public, the need to analyze the consumers arises. Through the years many different models of consumer categorization have emerged. Some of them were specific to their respective fields, others were general categories and processes that can be adapted to any design field. One very important categorization method was first introduced by Alan Cooper in 1999.

3.1 USER MODELLING In his work, “The Inmates are Running the Asylum”, Alan Cooper describes the fact that the high-tech industry has inadvertently put programmers and engineers in charge. Programmers and engineers run the show and end up being “back-seat drivers” for product development (Cooper, 2004). When Software engineers play the main part in the design decisions of a piece of software multiple problems emerge. Their background is in technology; thus, they tend to make software that has many features but proves very hard to use in the hands of the general public. Inexperienced users do not understand how to operate most of the systems’ functions and end up feeling confused or frustrated. Most companies release new versions of their software yearly in an attempt to provide the end user with an ever-increasing number of features, a “disease” called “Featuritis” by Tim Renczes (Renczes, 2004). The main reason that this problem exists, says Alan Cooper, lies in the fact that during the software creation process, programmers start the coding part right away. The design of the system takes place only at the end of the creation process, when most of what the software will be is already established. Programmers program for themselves, not the end user, they unknowingly make important design decisions during the coding phase. The decisions they make, have a negative impact in the overall design of the final product (Cooper, 2004). Cooper makes the case that software should be firstly designed by Interaction Designers and only after the initial throw-away prototyping phases of the design are completed should the programmers start the coding. Even though CEOs and software engineers find it difficult to throw away work that has been completed on the product, Interaction Designers understand it to be a necessity of the design process. The book naturally leads to the importance of Goal- Directed design, the kind of design that is focused on the consumer. He illustrated that software developed for

27 only one particular type of person will improve the chances of it succeeding. He suggests targeting the 10% and aiming to satisfy it by 100%, making them ecstatic about the product (Renczes, 2004). The use of personas is highlighted in this context, for its importance in the software design industry. Through the use of personas (where each persona should even have its own name), design becomes more consumer-centered. When personas are clearly defined, the design team will produce software for the individual needs of the persona, and will not fail into meeting the user needs. In most cases, Cooper suggests the use of three personas per project. If there is a need for more than three personas, he believes that the problem is too large and must be broken down further (Renczes, 2004). Through the formed character cast of clearly defined, a design taxonomy emerges that can provide fertile ground for design decisions. The next step comes through the use of scenarios. With the scenarios methodology, the design team gets closer to the personas and understands their needs more clearly. For this process: daily use, necessary use and edge case scenarios are advisable to be implemented. Every new feature the company decides to add should be viable in these scenarios to be considered for implementation (Cooper, 2004).

3.2 PLAYER MODELLING In a similar manner to Cooper’s suggestions, several design groups created taxonomies and ways to model the players of electronic games (Alessandro Canossa, 2009) (Darryl Charles, 2005). Two such researches are very relevant with the following project.

3.2.1 Play Personas In their work, Alessandro Canossa and Anders Drachen, illustrate that even though the suggested maximum number of personas is three for each problem space (Cooper, 2004), games are much more complicated systems that are targeted to a large audience with its specific needs and particularities (Alessandro Canossa, 2009). Through their suggested player modeling method called Play- personas, the duo suggests a different approach to user-centered game design. Since games are a medium with a focus on the development of emotional responses from the player, the main part of the experience is mostly depending on the end-user. Play – personas represent an adaptation of Cooper’s Persona framework for the games industry. According to their research, designers should provide players with a leeway for expression inside the game world. The players cannot be forced into emotional responses, since every one’s experience differs dramatically. Thus, emotional response cannot be assumed.

Play personas are not predictions of the users (like Cooper’s method), but are distilled form the direct personal experience of each individual player. This game- oriented personas are not only theoretical models of ideal users that have to be thought of by the designers, they are data-driven representations of real-world player behavior. The play personas contain data extracted from computer game engines during play. These metrics are called gameplay-metrics and measure a player’s interaction with the game. A variety of data is included here, from low level ones (such as button presses) to in-game behavior. The abilities a player uses, his hit chances, inventory management as well as the rate of deaths are all very common metrics. By examining different player types in the game Tomb Raider Underworld, a game that provides many different equally viable strategic approaches to player- game interaction, the researchers created their model. With play – personas, designers can create categories of player behaviors before a playable version of the game is complete, thus they can plan more coherent navigation and interaction modes. In their case study, they prove nine different archetypes or persona types that derived through play. This immediately shows the difference between other interactive media and games, in games multiple persona types already exist in the same gaming context. They clustered player abilities in regard to how well each persona interacted with the game world. Players with extraordinary shooting abilities were referred to as Grunts, those with expert jumping abilities were labeled Athletes, those with expert puzzle-solving abilities were described as Chess- Players. Through this categorization a possibility space of the persona types was developed and their differences were made clear. Each category of players was then given a narrative context as well as a procedural description. The narrative context is very similar to the one proposed by Cooper in his works. The procedural description though, is an explanation of the actual player skill in the game world. Through both these metrics, game designers are better able to create a more adaptable experience to every individual. Taking into account what different skills a game’s target audience will bring into the game, the developers can now more easily predict and plan out the game’s levels and encounters. In the conclusion of the research, it is proven that most of the player base not only is not predominantly into one single persona type, but evenly spread among the Hybrid types that lie in between the three extremes described before. So, creating games for standard, narrative focused personas is not as viable a method of player categorization as using play-personas is.

3.2.2 Dynamic Player Modelling The next step of the aforementioned research lies in the work by Darryl Charles and Michaela Black (Darryl Charles, 2005). In their research, a framework similar to play- personas is combined with adaptive games and online learning. According to their proposed framework, the steps that should be followed by the system that is responsible for the adaptability are categorized in on line and offline information about players. The offline information is two-fold. On the one side, there lies player modeling, the type of modeling is different in every project in regard to the type of game and the variety in gameplay methods. A model the team suggests is very similar to the Play- personas proposed by (Alessandro Canossa, 2009). It has less depth though, as it is only used as an example. The other offline information gathered is Player preference. Here the player sets his preferred difficulty for the ongoing game. The on-line system they propose is the main part of their research. Here they prove that only monitoring player performance through gameplay and helping or hindering the player is not enough. Proper game adaptation is much deeper than that. In order for a game to be more successful in adapting its elements to players more steps should be followed. After the initial monitoring of the players in the game, adaptability occurs, where the game gets harder or easier, depending on the player’s preference and the current performance. After the initial adaptation, its effectiveness should be measured through in-game metrics. Without measuring the effectiveness of the adaptation, the game cannot proceed in the next step, that of the player type re-modelling. In the player type remodeling part of the process, the initial models of the players are recalculated and the information of the current state of play is included. This is particularly important because games have a learning curve. After the initial understanding of the core gameplay, players will tend to develop their own gameplay style and playing habits (Schell, 2015). The circle of player monitoring and game adaptation is then repeated. The dynamic player remodeling system is also proven to make the learning curve of the game more efficient (Darryl Charles, 2005). Its usage, if implemented in a system, can make the learning part of the game a personal, tailored experience.

4 THE CASE FOR GAMES WITH MULTIPLE GAMEPLAY ELEMENTS

In recent years, we have been experiencing the Golden Age of Gaming, where thousands of titles ship every year, either in the form of AAA Games, or Indie ones. This is due to several major factors.

To start off, consoles were banned in China from 2000 to 2015, which by itself opened up a huge market for opportunities in the country. Secondly, games are now produced and sold via online means and not by hard copies, making distribution easier and cheaper. Lastly, the kids who grew up playing arcade games are now able to buy themselves the games they need and have since gotten into game design positions, aiding in the creation of new ones (Portnow, Extra Credits, n.d.). Following the growth of the player base, more and more game companies started appearing, and thus the current game industry was born.

In this Golden Age of Games, numerous game titles have since started investing in the incorporation of multiple gameplay elements in their games. Different gameplay elements make for more intricate experiences and enhance replay-ability.

4.1 WHAT ARE “MULTIPLE GAMEPLAY ELEMENTS”

"Game play is the formalized interaction that occurs when players follow the rules of a game and experience its system though play." (Zimmerman, 2003)

So, Gameplay is essentially a group of mechanics that indicate a way of playing. Mechanics that work together in cohesion, create a game dynamic that the player feels (Hunicke, 2004). Through this exact dynamic, play is created and maintained in the game world. For example, the racing games’ mechanics of car speed, ability to turn and stop or even throw projectiles against other adversaries, are distinct mechanics that in unison create the dynamic of the racing playstyle. In fps games, the player takes control of a character’s ability to run, strafe, shoot, jump and hide, all distinct mechanics that create a wholly different playstyle and experience. Although, both of these elements of play are harmoniously combined in games such

31 as the GTA Series by Rockstar games. The interpolation between the driving and gunning playstyle and the free roaming skirmishing playstyle.

Gameplay elements are not limited to platforming and fps, they can include from driving and shooting to multiplayer interactions and even social networking. Each group of mechanics that is designed to provide specific experience in a game will (for the purpose of clarity in this thesis) be considered both a Gameplay Element and a Playstyle.

By games with multiple gameplay elements, we refer to games that offer their players more than a single playstyle to interact with the game world. Since games are used as more than a pastime activity (Hunicke, 2004), they are more successful when they provide their audience with a multitude of ways to play. There really is no limit to the number of different playstyles that a game can offer and still feel coherent, as long as the player is not obligated to learn all of them. If the game has no dominant strategies in any one specific playstyle and all of them are equally viable ways to interact with the world, the game feels cohesive and enjoyable. If a game has a multitude of playstyles that all have to be understood for play to occur, it can be intimidating to new player, so it is better to be avoided. Multiple gameplay elements have to be introduced periodically into the game and time has to be provided so that the player can understand the basics of each playstyle.

There are a lot of reasons to create games with multiple elements. One such reason is to provide many alternative approaches to the game, thus making it an interesting experience for a broader range of players. Each player has his/her own background, and through player modeling we can understand that not everyone will enjoy the same kind of experience in a game (Darryl Charles, 2005). Another important reason to offer gameplay elements is the vast amount of replay-ability. Games that can be experienced in a multitude of ways can be replayed without losing much of their initial enjoyment. Interactive media such as the Fallout, Dark Souls and Elder Scroll series are widely praised for their variety of playstyles and replay-ability, with very large communities forming online to explain the differences and intricacies of each playstyle choice. Those communities formed from the players themselves, keep the franchises booming and profitable even years down the road (Bethesda, 2011) (From Sofware, 2011- 2016) (Softworks, 2008).

4.2 GAMES THAT MAKE USE OF MULTIPLE GAMEPLAY ELEMENTS

The most famous games produced during the last years (most of them conquered the “Game of the Year” title), contain multiple gameplay elements. Even though not stated as such in the descriptions of the games themselves, the following games in both the single and the multiplayer categories make use of multiple gameplay elements.

First category – Single player games

Single player games are the main focus of the thesis and the main system proposed will be developed for a single player gaming experience. As single player games, we mean games that are played by one person without extended interactions with other players online.

1. Dishonored In Dishonored, the player takes control of an elite assassin that fights to prove his innocence and expose a conspiracy in a post-apocalyptic kingdom. With Dishonored including gameplay elements such as combat, platforming, puzzles and quick-time events, the player is in risk of being overwhelmed by the multitude of choices and abilities. The game’s success, in my opinion stems from the fact that the developers created an ingenious learning curve. Play starts with an extremely simple wayfinding mission and a non-obligatory stealth tutorial in a form of a hide and seek game. What follows is a level beginning in a small isolated jail cell. Here, the tools the player has in his possession are limited, and no magical powers canbe used. After a couple levels, magic and teleportation are introduced in a dream, a place where the up-to-that-point experience the player has cannot be used to progress, and he has to adapt to the new playstyle. In conclusion, when the player has all the tools the game has to offer explained to him thoroughly through play, he can freely choose the playstyle he prefers and journey across the levels without limitations.

Dishonored – Arcane Studios

2. NieR Automata They multitude of playstyles theorem is more apparent in Platinum Game’s NieR Automata, where 2B, the main character is faced with the universe’s most bizarre enemies. The player will confront an abundance of different enemies that each have to be fought in a different way. One of the world’s first bullet-hell games in 3 dimensions, that has the player platforming her way through combat with large groups of enemies as well as gigantic constructs requiring more than precise timing to dodge and attack. And after these playstyles of platforming and attacking are clear to the player, new abilities and an in-game mini-game hacking system is implemented, changing the feeling of the game dramatically! One would suspect that so many different aspects of gameplay combined would confuse and frustrate players, but time proved differently. NieR Automata received the game of the year award and was praised by both the gaming community and reviewers, with scores ranging from 96% to 10/10.

NieR Automata – Platinum games

Second category – Multiplayer games

Even though multiplayer games will not be discussed thoroughly in the thesis, their importance cannot be ignored.

1. Massive Multiplayer Online Games For years now, ever since Everquest in1999, Massive multiplayer online (MMO) games offer a variety of different classes and playstyles to their customers. With the additions of trading systems, Player vs player battles, mount collections and Raids, MMO games have concretely proven that multiple gameplay elements are embraced by the fan base and their correct implementation in the game can increase the numbers of the game supporters. Seemingly taking the words of Alan Cooper by heart, successful MMO creators incorporate an abundance of new features that are actually used by the public, and not only by the game devs. “Featuritis” seems to have small impact in this part of the design industry.

Everquest with multiple extra screens to make gameplay management easier

2. Hero-Shooters A new trend of games that has been making a big impact on the game community for the past couple years is the Hero- Shooter genre of games. In Hero – shooters players play small matches (of usually 10-15 minutes) against another team of players online. They each choose a hero from a roster of different available champions. In contrast to single player games, in hero shooters, the multitude of gameplay mechanics emerges through the heroes themselves and not in the game world itself. Each hero presents vastly different abilities and each requires various skillsets from the player. With this model of games, designers create a battle ground that can incorporate players from dozens of gaming genres and can appeal to a greater audience. The most famous Hero shooter game to date is the 2016’s Overwatch. In Overwatch, a game with more than 30 million players (subsequently more than a billion dollars in revenue) in less than a year of release (Barret, 2017), more than 14 unique playstyles reside. Each hero in the roster requires different skills and are made thusly so that no matter the background of the player, he can play at least a couple of heroes with ease. Team Fortress 2 by Valve

Team Fortress 2 - Valve

Overwatch by Blizzard entertainment

4.3 A BRIEF INTRODUCTION TO FLOW THEORY In the games industry, there is this theory called “The flow theory”. The flow theory was first introduced by Csikszentmihalyi Mihaly in the early 2000’s. What Csikszentmihalyi proved was the existence of a state of being called flow, a state lying between high levels of stress and high levels of boredom, the place where people feel the maximum enjoyment that can be provided through a specific activity. (Csikszentmihalyi M. , 2000) Player experience in games can be represented in a two – dimensional graph, where the horizontal axis is the player skill and the vertical axis the game’s difficulty.

The horizontal axis, the skill axis, consists of player-specific metrics that have to do with the player’s overall performance in small increments of time. When beginning a new game, players start by learning the basics of the game’s mechanics. Their skill starts off relatively low and doesn’t really improve before the completion of the initial learning curve. After the first part of the game, when players can make informed decisions about their playstyle (even if they are not optimal), player skill fluctuates very differently for each of them. Player skill is not constant and is not constantly rising. The axis of difficulty – or axis of challenge – is the vertical part of the graph. The challenge the game puts before the players and the fluctuation predesigned by the team end up here. The more challenging an area of the game is, the higher the point in the graph. Challenge for the design team is a static metric, the higher the number, the more difficult encounters are. For players though, challenge is more personal, and the difficulty graph evolves into perceived difficulty. Perceived difficulty is the kind of challenge that the individual considers the game to be providing. What may be difficult for some can be easy for others. (Schell, 2015) When gaming, a player’s experience fluctuates between these two axes. A very important part of games is the amount of puzzle-solving activities they give their players. When the amount of puzzle- solving presented to the players is much less than their puzzle-solving abilities, it feels like a repetitive task that does not require

37 as much attention to complete. When the amount of difficulty is lower than the skill of the player, then the experience can become stale and boring. On the other hand, if a game is much harder or demanding from a player with relatively low skill, then the game becomes frustrating and the experience stressful. The player who has not yet discovered proper ways to interact with his encounters successfully, is more likely to be frustrated and the challenges presented to him by the game feel impossible to beat. Then the player usually stops playing. After all the gaming experience is meant to be an enjoyable past-time.

The margin between these two extremes of boredom and anxiety are the “sweet- spot” of user experience in games. This is called the “flow channel”. When in the flow channel, it is proven that players are riding the zenith of the experience the product has to offer. The highest state of immersion exists inside that state of play. Players in the flow channel perform much better in comparison to those feeling either unmotivated or stressed (Csikszentmihalyi M. , 2000).

Although being in the flow channel can produce incomparable immersion levels and satisfaction, simply having the player face slightly more difficult stages that are equal to his gameplaying ability will not worked for prolonged periods of time. The optimal fluctuation of the player’s journey through the flow channel is consisted of numerous difficulty curves full of tense and release cycles. In tense parts, the player is challenged at a rate that almost reaches the local anxiety area of the graph. Understandably, after a tense part of the game, the player has become better at the game since the challenge he just faced, was the hardest so far. Instead of the difficulty scaling right after the peak of the curve, it drops significantly, creating a release state where the player can relax and absorb the gameplay skills he has developed.

An ineffective difficulty curve An effective difficulty curve

According to Jenova Chen (Chen, 2007), the state of flow is defined by eight major components: 1. A challenging activity requiring skill Humans love challenge. But the challenge level should be at a point we believe we can succeed at. If we believe that we cannot achieve at the challenge we are faced with, taking into account our current skillset, we feel frustrated, and tend to turn to more rewarding activities (Schell, 2015). 2. A merging of action and awareness The player should be aware of his in-game surroundings, being able to interact with them with his avatar and having an impact. Not being able to understand his surroundings fully, breaks the immersion and frustrates the player. There is a fine balance to be achieved between no feedback and too much information on the screen. 3. Clear goals When the player goals are clear, he can more easily stay focused on his task. When the goals are unclear, the player is at a loss, as he does not know if his current actions are useful (Schell, 2015).

4. Direct, immediate feedback If the player, after every action he makes, has to wait to see what the effect of that action had in the game world, he quickly becomes distracted and loses focus in his task. If the feedback is immediate, the player can focus more clearly (Schell, 2015). 5. Concentration on the task at hand When the player is focused at the goal presented to him, he can become the best he can be in order to surpass the challenge. 6. A sense of control The player should have impact in the game world, the actions of the player should matter. When a player performs actions that have no effect in the game world, immersion is lessened and the player cannot stay in flow. 7. A loss of self- consciousness If the player forgets himself and projects into his character, full immersion is achieved. While fully immersed in the experience, the player gains the most emotional rewards the game has to offer. 8. An altered sense of time When in the flow state, players find themselves losing track of time. The concentration levels achieved at this point of immersion provide space for the player to play better.

Not all eight of the components have to be implemented in a game to keep players in their personal flow- zones (Csikszentmihalyi M. , 1990). Evidently, games are advised to mix and match several components of Flow in addition to their normal design process to improve player experience throughout (Chen, 2007).

4.3.1 Games want to keep players in the Flow Channel As mentioned earlier in this thesis, more and more games contain a plethora of different playstyles that players can opt for, most of which can be totally different between them (compare for example driving skill in the Watchdogs game by Bethesda to the hacking or shooting skills required by the player) (Bethesda, 2014). That, in essence, means that the calculation of multiple skills and player groups (if we are combining the players into player types through player modelling techniques), in combination with the numerous skills presented in the game can make it extremely difficult for the Design team to predict the proper difficulty of the game - namely, the vertical axis. The number of calculations required to satisfy all of the player base is enormous and thus on release the game is designed for a part of the player base (usually the most potentially profitable). Through the player’s journey into the game world his experience can be placed as a single point per increment of time in the graph. By playing the game, the player skill improves at a rate relative to his progress ratio (1-φ in the function of Y = KXn logφ where n = ) explained thoroughly in (Yelle, 1979) and- in reference to games- log2 bellow, in the section “Identifying the learning curve”. The progress ratio is different

40 for every individual, with groups of individuals presenting similar learning rates (Yelle, 1979), that means that before the game gets into the hands of the public, there is no knowing for certain how well each player will be in the game, and thus how fast the progress in player skill will be.

Games that aim to keep players in flow target player groups as suggested earlier. Through Beta testing and prototyping, the final products are created.

5 THE HYELIGHT SYSTEM

Establishing the need for a better difficulty system Regardless of the genre of the game, the need for an evolving and appropriate difficulty curve is essential to the player experience (Razavi, 2017). Games that can be rewarding regardless of the player skill will have greater appeal in the gaming audience. The author suggests a way in which games with multiple gameplay elements can approach and manage their difficulty curve. A tool that, if added to the game designer’s belt, can improve player immersion as well as increase the replay value of the game.

5.1 SYSTEM FUNDAMENTALS

Bellow, the main aspects of the design system are described in depth, along with the major design decisions behind each one. Included, are some suggestions on how each set of values can be understood by the game system. After the acquisition of the values, their usage is illustrated. From now on, the proposed system will be called Hyelight and referred to as such.

The Hyelight process consists of three parts: 1. Player Profiling 2. Targeted Dynamic Difficulty Adjustment 3. Game Balancing

5.1.1 Player Profiling

The first step in the Hyelight tool is to create and manage every player’s profile. The profile contains both online and offline information about the player. The inclusion of both methods of knowledge acquisition can greatly boost the accuracy of the adaptation (Darryl Charles, 2005). The offline information is collected from the player before play occurs, whereas online information is gathered according to player performance while playing.

The four main categories that the game needs to know about the player are: Preferred Playstyle (Online information):

This category of the profiling keeps track of the players’ mainly used playstyle. If the player progresses through the level by platforming from place to place instead of confronting multiple enemies, his playstyle link with platforming is enhanced. The reason this information is needed stems from the fact that if the player’s preferred playstyle is constantly rewarding and engaging, the player will remain in the flow channel for prolonged periods of time. Preferred playstyle can change and this

42 should be reflected on this value. The player profile is re-built constantly, based on the actions of the player in the game world.

Proposed ways to understand the preferred playstyle:

The game can count the amount of choices the player makes that include the same playstyle. When the player confronts any number of the enemies in the Area Cluster, that amount is divided by the total number of enemies in the Area Cluster. The same process can be used to count the number of puzzles solved per Area Cluster, or even the number of platforming completed. The result will be a percentage for each playstyle in the form of:

푁 푃 = % 푋 where:

P = Percentage of playstyle used in the current cluster

N = Number of choices of the currently counted playstyle

X = Number of total challenges in that playstyle within the current Area Cluster.

Results Analysis:

The metrics above will produce a number of percentile values equal to the number of playstyles in the game. Let’s call them PPlat for platforming, PComb for Combat and PNara for Narrative. Now these variables are compared to each other to deduce the preferred playstyle. I believe it safe to assume that if any of these values is over 80%, the playstyle is indeed one that the player enjoys, since he completed most of the challenges provided by the game in that regard.

System function:

With the results of PPlat, PNara and PComb, the Player’s profile now has made a ordering of the player’s preferred playstyle. The game manager uses this information to provide the next Area Cluster’s rewards. If the player profile presents a preference in the Combat part of the game, a new weapon can be awarded in the Area Cluster’s loot, if the player profile indicated high playtime in platforming, the ability to glide in the air or climb ledges will be the cluster’s reward. On the other hand, if the indicated value is narrative, a small side-quest or an item containing clues about the backstory of a Non-Player Character can be given to the player. Skill per Category (Online information):

This part of the player profiling process keeps track of the game’s different playstyles and the player’s skill in each of them. Depending on the different playstyles designed

43 within the game, the number of values can vary greatly. Knowledge on the current player’s ability to aim and dodge enemy attacks, will be recorded. Each distinct gameplay style should have its own counter in order to determine the accumulative skill of player. It is important for the game manager to distinguish between all the playstyles used, since adaptation is based on their individual values. Each skill per category is constantly updated inside the Area Cluster, through every choice the player makes. The metrics are not used before the next Area Cluster is created.

Proposed ways to understand Player Skill:

There are many pieces of software in the market such as Unity analytics that can produce accurate metrics of player skill and usage of the game. Many studios implement their own systems to keep data of their player base and rate the balance of their systems.

Depending on the type of playstyle currently being measured, the way the system will judge player skill can dramatically change. For the purpose of clarity, three distinct examples of playstyles and suggestions on them will be provided below.

Platforming Skill: Let us consider a game where the player can jump from platform to platform, grab and climb ledges while avoiding incoming obstacles such as bullets or rocks with a goal to reach a peak in the local geometry. In this scenario, the designers can make checks for total number of rocks the player hit while in the platforming stage, count the number of deaths the player accumulated by falling into chasms as well as the time it took for the player to reach his goal.

Time is preferably not counted in games that do not provide the players with agency to rush the course, since it can be very unreliable in cases where players take their time, have a break or are just admiring the scenery.

Combat Skill: Since combat skill has been measured in almost all dynamic difficulty systems, so the way to approach this kind of measurement is thoroughly documented (Harward, 2007). For combat to occur, many scripts and collision detection algorithms run constantly, providing designers a large pool of contents to collect data from. When measuring the combat skill of the player, metrics such as total damage inflicted, number of challengers beat, ability to headshot (if such a system is implemented), damage taken, number of deaths are very easy to collect. Another useful metric in this category is inventory management. If the player uses up a large amount of his items in a combat round, it has more than likely been a difficult one. Depending on the main goal of the game and the playstyle that the designers suggest, different data has different values. A game the encourages fast kills for example may count time used in combat, whereas games that promote strategic analysis and counterplay may wish to prioritize counting number of hits taken instead of time spent in combat.

Puzzle-Solving Skill: Puzzle solving is easy to measure as well. The game can count the time it took the player to complete every puzzle as well as the total number of mistakes or retries per puzzle. More complicated puzzles, such as area awareness or area clearing puzzles (with levers, buttons and patterns for example) have to rely on time based calculations more than number of tries, since their design is by default dependent on trial and error. Time is usually a value implemented in puzzle games in one or the other way, a good example of this is the hacking minigame of NieR Automata (Platinum Games, 2017), where the player’s spaceship has a limited amount of time to destroy the opponents. Another great example where player skill can be easily calculated, is Bioshock’s pipe connector puzzle game (Irrational, 2007).

Results analysis:

The way to understand individual playstyle skill is a little more complex than the preferred playstyle method described above. Every distinct challenge in the game, regardless of its requiring skill, has a predesigned difficulty.

There are numerous ways to translate raw data derived from player performance into quantitative values that can be used by the system. One of those ways is the ELO system, the famous chess player skill-balancing algorithm, another is the True skill system (Thomas, 2009) developed by Microsoft technologies for their gaming projects and last but not least the Glicko system (Glickman, 2016), an improved way to calculate player skill in chess and GO. All these models can be modified to be used by the game development team, a procedure usually followed by many companies that design multiplayer games. The creation of such a system is beyond the scope of this thesis, since it is a subject already in a very reliable state. In this context, it is used as a tool to work within the system under development.

During the design phase of the game, the developers that create each challenge, also mark it with a specific difficulty. When the player interacts with the challenge, his performance is compared to the hypothetical performance required to pass that part of the game. A score of the player skill is then produced depending on his overall performance in each skill playstyle. The results will be in the form of percentages, such as:

Combat_Skill = x %

Platforming_Skill = y %

Each percentile is marked depending on the design document of each team. For one game, an acceptable percentage might be that everyone over 85% score performed exceptionally well, while in another game only those performing over 95% should be considered exceptional.

System Function:

If the player is judged to be performing exceptionally well in one or more aspects of the game, the next Area Cluster is spawned with a harder difficulty setting for that specific skill. If his performance is less than optimal, the next Area Cluster will have its difficulty in that skill reduced. The basic concept that the results rely on is that they are quantitative data that can be compared to the current difficulty level do that adaptation can take place in the later stage of the process. Mood Choice (Offline information):

The mood choice, or Preferred Difficulty section is player input dictating the player’s current mood to be challenged. It controls the extents that difficulty can scale through gameplay. This design choice is based on the paper by (Justin T. Alexander, 2013) where the fact that difficulty should not always match maximum player ability was first proven. In addition, the presentation of player selected difficulty in the form of “mood” will make it easier for hardcore players to select an easier setup as well as allow casual players to try out more “hardcore” modes. The mood system is less psychologically threatening than “difficulty choice” and can be changed on the fly without making the player feel bad for opting for an easier difficulty, after all the goal is to ensure that the target audience’s desires are met – not the designer’s.

Results Analysis: The player is prompted to choose a mood between a pre-set group of properties. One of them is the “Relaxed” choice, indicating that the game will play smoother, the player will die less and the punishments will be less severe, a playthrough that can be more narrative focused than challenging ones. Another choice is the “Challenge me” mood, where the overall feeling of the game turns more stressful and the amount of challenge increases, an ideal setting for players that enjoy a challenge or want to test their skill limits. The “Relaxed” mode is more enjoyable by players that look for a more discovery focused playthrough, while “Challenge me” is better for achievers or challengers according to player models by Hunicke (Hunicke, 2004).

System Function:

When the player chooses a mood for his current playthrough, the game’s overall difficulty range is reduced. Depending on the mood choice, this reduction can make the game harder or easier and presents a new range that the system should work with. In a difficulty system that ranks from 1 to 10, when the player chooses the “relaxed” mood, adjustment will occur only between 1 to 6, instead of the whole difficulty range. In the “Challenge me” mood choice the ranking is contained between the 4-10 values. The reasoning behind the range choices is personal estimation and should be directed by the game design team that produces the experience, since all games are and feel different.

Estimated Player Frustration (Online information):

This value is the combination of various counters that have to do with player frustration, all of which get renewed after every Area Cluster (described below). This value can consist of the total count of player quits, deaths and retries of parts of the Area made by the player, as well as number of supplies expended during their playthrough. Much research concerning psychophysiological methods that can be measured and produce reliable values for player satisfaction and frustration exist (Drachen, July 2010) (Regan L. Mandryk, March 2011) and their implementation on the process can provide more accurate results and adaptability.

A simple way to calculate accumulated stress in this system, is the graph of the performance rate of the player, a graph that indicates how the player progresses through the game. If performance has drastically declined for a prolonged period after a number of Area clusters, there is a good chance the player is either tired or frustrated, resulting in a decrease in enjoyment of the activity.

Provided that the estimation of player frustration is accurate, several benefits emerge. The game can make better informed decisions about the following Area Cluster’s reward settings and keep the player in flow for longer. The scope of the current research does not include a metric for player frustration, but it is a topic for future works on the process, since its implementation can aid the model substantially. It is nevertheless added in this part of the process, since its usage should be explained. For the purposes of the evaluation, player reactions were analysed and they were asked to explain the parts during which they felt too stressed or too bored.

System Function:

When the game manager can understand levels of player frustration there are several ways to respond to that. Firstly, if the player is running low on items, increased drop rate can provide him with some short-term reward. Since the reasons for player stress stem from the difficulty part of the game and perceived challenge (Harward, 2007), a good way to relieve stress in the game world would be a lower difficulty region of play. Thus, it is suggested that the difficulty for the first part of the next Area Cluster should be lessened.

Other ways that could help alleviate stress can be implemented through procedural rewards. These rewards can be spectacle or praise rewards, as indicated by Jesse Schell (Schell, 2015). Offering small rewards to the player is confidence boosting and can renew the player will to continue his journey in the game world, even after multiple instances of failure. While rewards can be implemented after the player completed a certain number of Area Clusters, this type of reward should be ideally awarded after completing a particularly self-challenging portion of the game (according to player performance instead of a pre-set point in time). Through judging

47 the player’s skill, the system knows when he has completed a personally challenging portion of the game and can opt to offer the targeted reward at that point in time, just after the completion of the Area.

5.2 TARGETED DYNAMIC DIFFICULTY ADJUSTMENT

In Hyelight, Dynamic Difficulty Adjustment (DDA) is treated differently than other difficulty settings in use thus far in the Games industry. Hyelight’s DDA system will from now on be referred to as TDDA, or Targeted Dynamic Difficulty Adjustment. TDDA’s main feature that differentiates it from other systems is the rate of adjustment. In TDDA, adjustment happens once in every predetermined area cluster of a level within a game. In essence, what this means is that once the player enters a new area of the game, based on the factors analyzed bellow, the specific area of the game gets assigned a specific difficulty. Once the area has been cleared, the next one is created with the renewed set of parameters derived from the player profile.

5.2.1 Area Clustering

In order for the Hyelight process to work, game designers along with level designers break down each level in various area clusters. Area clusters are created based on the desired difficulty scaling per area. What this method of creating a level provides to designers is the reduction of dynamic adjustments within parts of the game that need to feel continuous as to not break the player’s immersion.

For example, imagine that the player enters a haunted tower to face the level’s final boss. The boss room resides on the top floor of the structure, guarded by a number of enemies suggested by the game’s current difficulty state, the strength of the boss is dependent on the difficulty curve in effect (explained later on in this thesis). When the player first tries to reach the boss room, he will most likely fail, since a boss is usually represented by a local peak on the difficulty curve. After multiple failures, the system will not adjust the total difficulty of the specific Area cluster, since the player might feel cheated out of an opportunity to confront the enemy “as intended”. We should not risk the players feeling that the game is “going easy” on them since this is one of the most negative effects of DDA systems. As mentioned earlier, the world will feel less real, making the player lose their immersion.

The individual size of each Cluster depends entirely on the design decisions made by the team. Larger Area Cluster sizes have the benefit of a more stable immersive experience, whereas smaller Area Clusters provide a more closely adjusted difficulty rating. This is due to the fact that Cluster difficulty is constant with predetermined differentiations between encounters (representative of the difficulty curve fluctuation).

5.2.2 Difficulty Curve

In the Hyelight process, dynamic adjustment isn’t the only aspect of difficulty fluctuation. For immersive gameplay that plays and feels right, a difficulty curve system exists within the confounds of the system. There are some differences between conventional difficulty curves and the one proposed here.

The proposed difficulty curve is not a fixed one, that is to say, there is no constant curve that applies to all players equally. This difficulty curve is a combination of many smaller curves called “fractal curves”.

To start off, the game’s designers create the experience they intend to convey with the difficulty curve the way they would normally do. This difficulty curve is then broken to smaller tense and release cycles according to local peaks and valleys of estimated player stress that it presents. Each one of those smaller pieces of the overall curve is implemented as a metric for adjustment in each Area Cluster previously defined.

Using this methodology, a great advantage immerges: since the game can now understand the level of mastery the players have, it can provide them with the appropriate local curve height at any given time. Through measuring the progress made by each player, a record of their successes and failures will be kept for each Area Cluster. Overall great success in all gameplay elements of an Area Cluster means that the player is currently stressed to a minimum and the player model should be informed. The following Area Cluster should then have a higher overall difficulty.

Each part of an Area cluster can be set to challenge the specific player by a preset amount, making the game’s difficulty count not an overall difficulty, but perceived difficulty, an appropriate metric for each individual player. This is the main benefit of the Hyelight system contrary to standard dynamic difficulty adjustment systems. The Designer can create a custom curve within each cluster, since they are sure that the cluster’s difficulty will remain unchanged relative to itself.

When the difficulty curve of an area cluster is created, designers can sketch out the exact challenge they desire each of their players to face. If they want a cluster to start with a difficulty less than the player’s skill, adjust to difficulty equal to player’s skill in the middle and by the end have a “boss” encounter slightly harder than their skill so that it feels like an appropriate challenge to the individual, it can all happen with the use of the fractal curves mechanism. The look of each curve should be an array of numbers that indicate difficulty fluctuations in the area cluster.

The final difficulty curve of the game, is no more than the combination of smaller fractal curves spread evenly through the Area Clusters of the game world. There are though several factors that designers have to consider when creating the difficulty

49 curve for the Hyelight system. The guidelines that were produced during the system’s evaluation are indicated below:

1. The fractal curves created should focus mainly on the range of difficulty between each local valley, to each local peak. Usually a culmination from low to high, so that when difficulty is applied in the Area Clusters, the player always starts at a resting point rather than a stressful encounter, moves to play the appropriate difficulty and finally encounters a challenging part so that his skill can improve. 2. There are x number of fractal curves per Area Cluster, where x is the number of all the available playstyles in the game. That means that each Area cluster has the same amount of choices for every gameplay element of the game, and each fractal curve should represent that. 3. It is advisable not to make the difficulty of all the gameplay elements the same, because it can lead to excessively stressful or boring areas.

5.2.3 Adaptation

The rate of the increase or decrease (in case the player is underperforming) in difficulty depends on the rating of player performance. The rating of the player performance is provided by the system behavior described in the section “Skill Per Category”. Depending on the design decisions about how the game should play out, each team creates the boundaries of difficulty for each playstyle they provide in their game. These boundaries in difficulty should be calculated as integers of small ranges such as 1 to 6 or 1 to 10, depending on the levels of depth the developers desire to put into their game.

If the player performs within the 40% to 60% percentile margin of the expected behavior, the game is considered to be in a balanced state and will not adjust further. If the player is judged to be performing exceptionally well or extremely poorly (percentiles of less than 20% or more than 80%, depending on the team) the specific category should be increased by 2. In all other cases, the difficulty of each specific skill should be adjusted by 1, to either a lower or a higher value, depending on player performance. The rate of 1 ensures that even though difficulty will be tempered with, it will not be game-breaking since let us not forget that the difficulty curve of the Area Cluster will be involved in the final adaptation.

5.3 HYPOTHESES ON THE PLAYER EXPERIENCE Before the testing of the prototype, according to the research and methodology provided above, several hypotheses are made.

1. Players will remain in flow for prolonged periods of time if the game’s difficulty changes according to their expertise in certain areas of the game, contrary to the difficulty adjustments occurring over all aspects of the game. Because the individual skill of every playstyle will be judged and clustered separately, the players will feel that adaptation takes place in a more natural and tailored way.

2. Enjoyment of a game will increase if the game’s difficulty curve adjusts to the rate of improvement of the player. When players improve in one of their skills, the game element that has to do with that skill becomes harder, providing an appropriate challenge for them. Through the implementation of the Fractal Difficulty Curve, the game’s designers will have control over the challenge level their players go experience.

3. User experience is augmented if the players can themselves choose the challenge level they desire in combination with a DDA system. This way players can opt for a more relaxing or more difficult playthrough if they want to.

4. Immersion will remain stable because of the Area Clustering system. The rate of adjustment is spread apart enough that the player will not feel like the game is cheating him since the enemies, once encountered, keep the same difficulty.

5.4 HYELIGHT CONCEPT MODEL The interactions between each component of the Hyelight system are highlighted bellow in this extensive concept model. It includes the player journey as well the mechanisms that are hard at work to keep them in flow.

6 TESTBED, HYELIGHT

One of the testbeds used to test the Hyelight system will be a brand-new game created for the purpose of this research. The main reason a new game was developed stems from the fact that it was very difficult to find a game that can be used to test the hypothesis. Even games that use mods contain many gameplay elements that will only confuse testers into not concentrating on the game’s difficulty and instead focusing on parameters that are not a part of the evaluation. The game is evidently named “Hyelight” and its design process went as follows:

6.1 STORY After the death of a person, he or she is transferred to the realm of the gods to be judged according to the life they led. If the individual has proven herself as an immaculate human being, then and only then can she escape the circle of birth and rebirth and join the heavens. If she is judged as less than human, she is returned to earth in the form of an animal so as to go through it all once again. The protagonist’s name is Sinn, a recently deceased human princess, whose soul is judged by the gods in their heavenly realm. She is slowly turning into a fox, since her spirit is weakening. Her actions on the heavens can provide her with a worthy afterlife or a return to earth as a fox-spirit. Reaching the temple of the gods and getting to enter it, will restore her to life and give her a second chance in the afterlife.

6.2 DESIGN For Hyelight to become a reality, a long design process was followed. Firstly, gameplay was decided upon the basis of the Hyelight System, the game required different gameplay elements that each would be judged individually. Concept art of the world and the different characters was created. Then the characters were modeled, rigged and animated. Once they were ready, coding in unity began. After an arduous journey into the programming world, a set of modular level design pieces was designed. The first map of the game came to life along with Visual effects created from scratch.

6.2.1 Concept art In the initial concept phase, Hyelight was supposed to be set in a medieval setting. After careful consideration of the overall aesthetics of the game and my current mood, I decided to opt for something a little more challenging. Some early ideas included a post-apocalyptic world with very limited technology, some others a dystopian city in smoke, dust and electricity floating around. After a lengthy discussion with a close friend, where we compared the differences between heaven from an eastern and western perspectives, Hyelight’s heavenly realm was born. We envisioned it as floating castles in the clouds, a place where the dead could show their values and be judged accordingly. A place where a form of gods resided. The

53 gods were thought of as a form contrary to humans, spirits and animals, since they are perceived as foreign and scary from Hyelight herself.

6.2.2 Art Style and early experimentation In the early stages of the concept, the art style was very different. The hero model was way more detailed and intricate. The first Hyelight princess was more like a human warrior samurai, fighting with a katana against electronic enemies that used technologically advanced weapons and devices. The art style was more realistic and this shows in the first animated model created. She had over 25 separate animations and interactions. She was fully animated with physics-controlled parts.

Animation sequence stills

Her texturing was done in Substance Painter, and scratches, weathering effects, bump maps and even procedural roughness was included. With the roughness maps, light bounces differently on every part of the character. Due to the amount of time required to complete the whole game world with similar assets being extremely large, it was decided that the semi-realistic art-style should be dropped in favor of the Hyelight “minimum viable product”.

Final Texture for Sinn, low quality real-time render.

6.2.3 Main Character and Final Art- Style Sinn, the heroine of the game, is an Asian princess that is trying to escape from heaven. She is fox- like in appearance and carries with her a pink umbrella. After her death, her spirit was judged not to be strong enough to escape Samsara, or the circle of existence forcing her into a more primitive lifeform, like that of a fox. Through her journey in heaven, she is confronted with enemies that should prove challenging enough for her soul to handle. If she manages to overcome the tasks set ahead of her, she may escape heaven and be given another chance in life as a human.

For the final look of the princess, the low- polygon design style was implemented, keeping the number of triangles in the game world to a minimum. This way, the assets could be produced in a much faster pace, allowing for more time to iterate on the design of the Hyelight System rather than 3d animation and modeling.

Sinn final look and color scheme

6.2.4 Animation The hero model contains 15 animation sequences, that range from idle and jump up to spell casting and floating. All enemy models also contain a minimum of 5 animations, with 2 attack patterns each. For the implementation of all the animations, Autodesk’s Maya and 3ds Max were used each for the excellent toolset it provides. The rigging of all deformable characters, as well as the control layers and deformation control scheme was created from scratch by myself for this specific project, testing muscle and CAT systems in 3ds Max’s bone system.

Skinning and Rigging Sinn in 3ds max

Double Jump and Death Animations

6.2.5 Enemies There are 2 different enemy models in the game. Both were inspired from a mix between constructs and steampunk engines along with a Japanese aesthetic. The concept behind the enemy models were that they should be representative of humans, but at the same time not be biological lifeforms. The construct nature of the enemies makes them look humanoid, while at the same time making them feel unnatural and different to Sinn, a half- human half- fox hybrid.

The first is a lighter type of enemy that shoots bullets that follow the player around. The light type of enemy is equipped with two cannons instead of hands and is encountered offline- meditating on the floor of the game world. Once the player moves close enough, the enemy recognizes her and starts shooting. This type of enemy is easier to kill, but a great number of them at the same time can pose a big threat. He has two distinct moves. A fast bullet shot and a strong double bullet shot. When the player Shields herself, the bullets are destroyed and when she dodges, the bullets miss her and stop following her. In lower difficulties, they die with one melee stroke, but in the highest ones, one of their shots causes damage equal to half the player’s health points and they take up to 4 hits to die.

The second type of enemy is a brute type enemy. A large construct with a huge naginata as its main weapon. The brute oversees heaven and watches that souls do not try to escape. When it encounters the player, it moves towards her and slices in her direction with either a fast double-slice, or a slower but more impactful ground slam. This enemy is much stronger and with a larger health pool. More than a couple of them together can become a very serious threat to the player, causing instant death. Lower difficulty brutes have a smaller chance to hit with their strong attack, while higher difficulty ones have more than double the health points.

Brute and Light enemies

6.2.6 The World The game takes place in an otherworldly environment, where a small settlement is located inside a nebula. The settlement’s architecture is based off Japanese and Chinese architectural schemes. The world is supposed to represent the gateway to the great Temple. Once dying souls reach the Temple they have proven their ability and are allowed to ask for a new chance in life as a human being. A great source of inspiration for this project were the works of nocras and their Oriental Express series of paintings (nocras, 2017). The final implementation due to lack of time and resources was the minimum that the game world required to feel like a functioning game, only containing a small amount of extra assets as well as indoor locations.

All of the game’s assets were created with the modular kit workflow, where a group of walls, floors, windows, trees and columns were designed first. By combining all the modular pieces together, a very large amount of different assets could be created, from bridges, tall and short houses with balconies, as well as stables, staircases and walkways. Thanks to the modularity of the game’s 3d models, much less work was required after the initial whitebox stage of the level design.

All the game’s assets in their modular look

All the game’s assets’ colors derive from the same UV map, so there is minimum usage of processing power to color and light every surface in the game. By changing the UV map, the game’s whole color scheme can change instantly without post processing effects needing to be applied. This method allows for direct control over each vertex’s color independently, or it can be used to change the whole color scheme.

Texture modification tests through a single UV Sheet

6.2.7 Visual Effects All the visual effects were created by me as well, solely for the purpose of this project. There is a total of 15 visual effects in place. Ranging from fireball and slash attacks, to sakura blossoms falling and healing shrines. Most of them are minimalistic in nature, with simple cubes that change form and colors, others are more complex such as the Heavy Brute attack that creates a fissure in the ground, followed by fire explosions and cracks.

Electric Orb and red Fireball

Shrine Full of Light and Healing Orbs

Electric Damage ball and Fire Fissure

Tail Slash and blue Fireball

Sakura petals falling

6.3 GAMEPLAY In Hyelight, the player takes control of the main characters’ psyche and is faced with numerous encounters. There are two different playstyles the player can opt for, one is the platforming playstyle, the other is combat, making this a very simple game with multiple gameplay elements.

6.3.1 Platforming Hyelight is full of platforms and ledges where the player can jump or glide to. There are numerous challenges to face, from moving platforms to ones that fall after a while. The tools in Hyelight’s disposal consist of an array of jumps. She can jump, double jump and glide through the air to reach her destination. The jumps are higher than those of an everyday human, so that the player feels less encumbered to move around and explore. In platforming, there are several factors that can scale the game’s difficulty. Platform placement: the number and location of each platform changes the difficulty dramatically. From very simple gaps crafted by adjacent platforms to extremely long gaps, the designer can experiment with all sorts of distances between the jump pads to better suit the fractal difficulty curve he is designing for. Platform stability: When platforms are not stable, they can either move in certain directions, rotate around themselves, or even drop after a preset amount of time. The combination of both moving and static platforms is required for a more varying game experience. Platform size: This one is pretty much self-explanatory, when platforms are smaller, they require more precise-landing skills form the player. When the platforms are larger, they are easier to land on. On large platforms, other types of encounters can be contained, such as enemy groups.

6.3.2 Combat Combat in Hyelight is simple enough for a player to learn in a single playthrough, but it can take a bit of time to master. The hero can perform four combat actions. She can attack with a melee slash, she can throw a projectile, she can become air to dodge an enemy attack and she can produce a shield to absorb enemy shots. Health: Hyelight has a health bar, every enemy attack reduces her current health depending on the enemy’s strength. If her total health is reduced to zero, she dies. The slash: The slash is the main damage the player will be able to perform, with a swing of her tail she slashes enemies in front of her in an arc. The damage done is static through the gameplay section, so that the player doesn’t feel like damage is inconsistent. The slash has a very short ability cooldown and can only hurt enemies that are very close to her.

The Shield: Sinn can use her power to surround herself with a protective barrier that destroys bullets and blocks enemy attacks, but leaves her unable to attack. This defensive option is on a 5 second cooldown, but does not require stamina to use.

The Fireball: Behind Sinn, a maximum of five lanterns float in a circular motion. Each of those lanterns contains fire that she can rain down upon her enemies from a distance. She has a limited amount of these projectiles, equal to the number of her total floating lanterns. Once an attack has been performed, a lantern fades out. When coming in contact with a shrine, the lanterns refill, giving her the ability to strike again. Those abilities cannot be spammed (used repeatedly), since they are stronger than her slashes. Only by using these attacks can Hyelight harm cannons.

Becoming ethereal: If the player is focused, he can make the hero immune to damage for a short amount of time. If within that limited time Hyelight is hit, she ignores any damage dealt to her. Becoming ethereal costs stamina, the green bar accompanying her health bar. Every time she dodges an attack, she loses a bit of stamina. Dodging has a small cool down time.

Stamina: The stamina bar is a green bar that refills as time goes by. When stamina is depleted, the player cannot dodge or attack. It is a resource that adds an element of resource management for the player, that unless managed properly, will be easily depleted, leaving the character out of breath, defenseless.

6.3.3 Bullet Hell elements In Hyelight there are numerous turrets lying around the level. Those turrets shoot electrical orbs in patterns. On contact with the orbs, the player takes damage. The patterns are fully controlled through the difficulty manager and change depending on the difficulty of the current curve. In par with games like Perfect Cherry Blossom or NieR Automata, the minigame requires platforming skills from the player to move around the environment. Bullet hell elements were implemented as an extra element that can control the game’s overall difficulty, by also having the benefit that it can be quite easily adjusted. It does not require combat skills from the player, so it is controlled fully by the platforming ability that resides in the player profile.

The choice to include a bullet hell element into the testbed began when development started. In the beginning, it was supposed to be an extra gameplay mechanic to be judged and adapted according to player skill. After testing, it was decided to include bullet hell elements to the platforming part of the game, making it easier to design levels and difficulty clusters. The number of bullets, their damage and patterns, when combined with the platforming skill of the player, it becomes considerably easier to create a well-balanced experience for that part of the game. Patterns: there are two types of cannons in the game, the solo-cannons and the multi-cannons. The solo-cannons, as the name implies, are composed by a single cannon that either shoots the player or a stationary target preset in the game world. The multi-cannons shoot in predetermined patterns in four directions at the same time, but do not target the player directly. The multi- cannons’ role in the game world is to make the player consider their overall movement and shield usage more carefully. All the cannons are equipped with a script that enables them to move around in order to create even more complex attack patterns, thus more difficult levels. Projectiles: The projectiles of the cannons are different in color to those of the main enemies, in order for the player to understand the difference in dodging each of those. They cause more damage than the enemy bullets as well, since their main reason to exist is to make the platforming experience more formidable, but are much easier to dodge than the homing projectiles spawned by the main enemies of the game.

Flower like bullet patterns

6.3.4 Data collection and profile analysis Based on the research previously covered, a player profile was deemed important to create. Considering the advice provided in the Play- personas (Alessandro Canossa, 2009) and Player modeling for adaptive digital games (Darryl Charles, 2005) papers the Hyelight’s player profiles were created. In the player profile, all the important variables from each player’s playthrough are stored. During gameplay, the Game manager creates an excel file that records the current playthrough. In each specific file, each different player’s experience is recorded.

The file is divided in clusters. Each cluster contains information about the player’s overall skill in each of the two different playstyles available, platforming and combat. Player skill is stored in percentages deriving from the difficulty calculation algorithm (see Difficulty Manager). Every variable that plays a role in the calculation of the player’s skill is also included under each cluster’s name.

The algorithm used to calculate true player skill for platforming and combat is the one in the last pages of the thesis, in chapter 7.4.

Through these variables, the researcher can determine a number of things:

1. If the Difficulty manager adapted the player correctly.

If the difficulty calculation was successful or not, can be easily calculated by combining research data. Provided enough players managed to score between 40%-60% in each of the two playstyles in at least a single cluster, the difficulty calculation will be considered a success. What a score of 40-60% in each playstyle essentially means is that the player reached his skill cap. This score should be ideally achieved by the time the player reaches the third game cluster, since the first cluster is created to generally place the player’s skill in each category, while the second cluster will place the player closer to his skill-cap. If the player does not reach this middle ground, it proves that the system is created incorrectly and needs to be reworked. If the player scores much lower in a cluster following an average scored one, it means that either the system is incorrect, or that the level is created unequally.

The reason some players may constantly higher than 60% might mean one of two things:

One being that the player has a very high skill-cap, one that is not covered in the current game (in short, the game is too easy for them). The other case might be that the model overestimates player skill and should be recalculated (especially if players complain about the game being too difficult, while still scoring high).

2. If the player improved slightly or significantly during gameplay

While calculating player ability and skill, if the player improved his score between the second and third cluster, that means that their specific skill was increased through play, improving their skill-cap. The score of the first cluster should not be considered of importance, since its difficulty is predetermined and the same for all players, its main goal being to place player skill within boundaries.

When compared to static difficulties, this way the researcher may also determine if the players improve their skillset in a faster rate when TDDA difficulty is applied.

3. The area of expertise of each player.

The player profile can provide important information that can be used to understand each participant’s area of expertise in the game. This piece of information can tie nicely with the questionnaires part of the evaluation process. It will be interesting to observe if players claiming to be good at combat prove to be better in platforming or vice-versa. This can also provide a great metric to compare players to each other and understand better the differences between hardcore and casual players and if their self-assessment will be as accurate as Justin T. Alexander prove in his paper (Justin T. Alexander, 2013).

6.3.5 Area Clusters Following the directions of the Hyelight model, the game consists of three clusters, named: The Entrance to Heaven, the Village and the Temple, according to their location. As an important note, I should add that the number of the clusters is derived from the total span of the level and not the story or locations in the game!

Each cluster contains at least one platforming region, and either two or three combat encounters. The platforming regions each have six different difficulty states, one for each difficulty setting in the game. Their difficulty depends on platform placement, cannon number and patterns as well as platform sizes (as described in an earlier chapter). The combat regions spawn groups of enemies in predetermined areas, with the total number of enemy combinations being 18. The reason the number of enemy spawns not being 6, and equal to the total number of available difficulties, but 18 gives the opportunity for the designer to create Hyelight’s Fractal difficulty curves.

6.3.6 Fractal Curves As per the Hyelight model, the game was created with the freedom provided by fractal difficulty curves. Instead of designing a large difficulty curve spanning through the whole game, each region got their own difficulty curve as input.

Each fractal curve has the length equal to the length of each cluster. Since each Area Cluster contains up to three combat encounters, the player should feel that they are playing an evolving game, thus being on a curve instead of being pushed to their skill limits (Adams, 2008). To provide this scaling in difficulty within the same cluster, the first combat plays the role of the “introductory challenge”, the enemies that spawn are weaker than the player’s true skill, and serve as an introduction to the area as well as a stress relief mechanism (since the player just passed a stressful part of the game) (Schell, 2015) (Razavi, 2017).

The second combat corresponds to the players’ true skill and can be considered the “True challenge”, enemies encountered here are as powerful as the player should be able to handle and provide a moderate challenge, while preparing the player for the last part of the cluster.

The third combat encounter in every cluster corresponds to the “boss fight” level, the combat that pushes player skill to its’ extreme, providing a challenging yet fair encounter. Player stress after this combat should be high enough that a lower difficulty should follow, namely, the “introductory challenge”. Thus, completing the circle of stress- relief the player should go through to cruise the “Flow channel” (Chen, 2007).

6.3.7 Difficulty manager The Difficulty Manager is an algorithm that has a multitude of uses in the Gameworld. It is essentially the master puppeteer that moves the strings of play in the world. Through the Difficulty Manager, the most important gameplay elements are enhanced and managed. It is included at the last part of this thesis in script form. True skill calculation

The first thing the Difficulty Manager does is calculate the player’s true skill. A player’s true skill is calculated through the difficulty calculation algorithm of the game. The Difficulty Calculation Algorithm of this specific game was based on the model by E. Yelle as well as a combination of the different variables collected in the player profile.

A player’s true skill is calculated separately for the combat and platforming skills of each individual. The Combat skill of the player is calculated a total of four times in each cluster, once after every combat and once at the end of the Cluster. The first three calculations are needed for the fourth one, the last calculation is the one that calculates the player’s true skill and score for each cluster.

The second calculation, the one that is made after the “True challenge” encounter, is that of the highest importance. The first and third encounters are less important while calculating player skill, so to calculate true combat skill, the following function is implemented: 퐸1 + 2 ∗ 퐸2 + 퐸3 퐶표푚푏푎푡푆푘푖푙푙 = % 4 Where E1, E2 and E3 are Encounters 1 to 3 respectively. By giving more weight to the second part of the encounters, the player is punished less for being bad at the hardest part of the game and receives smaller compensation for being good at the first ad easier encounter.

In order to calculate the true platforming skill, all variables that have to do with one’s ability to run, dodge and shield bullets are calculated once in every cluster (since fractal curving was not included in the platforming part of the game, because it proved to be extremely time-consuming). Both of these skill calculation algorithms can be found at the end of this thesis. Cluster Difficulty

Depending on each player’s true skill, the Difficulty Manager sets the pace for the next Area cluster.

If the player scored less than 16% the next cluster is spawned with a difficulty 2 degrees lower than the current difficulty. If the player scored between 16% -39% the next cluster’s difficulty is reduced by 1. If the player scored between 40%- 60%, the difficulty remains the same. If the player scored between 61% - 84% the difficulty increases by a single degree. Finally, if the player performed exceptionally and scored more than 84% the next Area Cluster is spawned with an increase of 2 degrees.

The difficulty is of course different depending on each available playstyle. Each area’s difficulty is both the platforming and the combat difficulty.

For this specific game, the total number of available difficulties ranges from 1 to 6. So scoring very low on a setting of difficulty 1 means that the player is not in the game’s

72 targeted audience, same applies for players that score exceptionally well when the difficulty is set to 6.

There are 24 different platforming difficulties and 18 distinct combat encounters in the game, making for a game with 24 x 18 = 432 different gameplay possibilities and combinations, always tailored to the player skill.

7 SYSTEM EVALUATION

To test the system proposed in this thesis, three different games were used. Each game was picked for a different reason and tested in a different manner. The first evaluation was planned to be completed using the Dishonored 2 game by Arcane Studios. This game was picked to help test the player reward system that exists in the confines of Hyelight, since it has a variety of tools that allow player interference in its difficulty. The second test was completed in the Dungeons and Dragons (3rd edition) game, a pen and paper board game. Even though not a digital product, by testing the system on a completely different environment, full of a variety of gameplay features and a multiplayer setting, many interesting observations emerged. Lastly, the system was tested through the game that was created for this thesis. The last test is the one of the utmost importance, since it would take place in an environment created from scratch with the Hyelight system in mind.

7.1 FIRST SYSTEM TEST- DISHONORED 2 The first game to be used as a testbed was Arcane Studios’ Dishonored 2. This game is famous for the many different difficulty settings it provides the players with as well as the abundance of ways to approach every given situation in game. What follows is the game’s analysis as well as the process that should be used for the evaluation process. Unfortunately, due to lack of time, this system evaluation was not completed for this thesis. Either way, I included the research done in the game so that the evaluation can be completed in the future if it is required.

7.1.1 Gameplay In Dishonored you take control of an assassin and play different missions to discover clues about an evil empress. Even though the game offers two different characters the players can opt for, for the purpose of this thesis, subjects were prompted to play as “Emily” only. This decision was made so that results from different players can be compared to each other. As discussed earlier, Dishonored is a game with multiple gameplay elements. Players can opt for different playstyles, all of the equally viable as gameplay methods. The first playstyle is Stealth. Using the stealth playstyle, players are challenged to

73 eliminate their enemies either by killing or knocking them out while going unnoticed and sounding no alarms. After the player gets access to super powers, they can decide to climb in off-sight ledges and balconies so as to face much less enemies. The second playstyle is the combatant style. Players can opt to fight guards in melee combat using a variety of weapons and powers. While in the combat playstyle, guards can fight, flee, or call for reinforcements. Even though the game gives special narrative rewards to players that play extremely stealthy (never get spotted by an enemy), or in a merciful manner (never kill an enemy), for the purposes of this research players were informed that these rewards were not included and were encouraged to play the way they preferred.

7.1.2 Level division and Area Clusters Dishonored 2 is a game that divides gameplay into smaller levels. For this test, the players were asked to play 3 levels. The tutorial stage, so that they understand the basics of stealth, combat and powers, then the first and second level.

The first level was divided in three Area Clusters, the Mansion, the Streets and the Docs. These Areas have clear borders between them, with a single way to move between each one. Each Area cluster contains both of the main gameplay approaches. Since it is the first level, the player does not have any special powers.

The second level was divided in three Area Clusters as well. The First hostile territory and Past the wall of light. The entrance to the second cluster was triggered by passing the wall of light in any of the available routes. Each Cluster contains both combat and stealth encounters and the player can unlock up to 2 special powers.

7.1.3 Difficulty Curves After careful observation and in-depth testing of the first 2 levels in “Dishonored 2”, the following predesigned curves were discovered. Both level curves were numbered from 1 to 6, where 1 represents easy difficulty and 6 hard. The difficulty curve was calculated in the in-game suggested experience called “Medium Difficulty” with all presets such as enemy perception and footstep noise in the average values. The combat difficulty was calculated according to the number of enemies, the amount of alarms in an area, the powers of the enemies encountered such as their variety in weapons and attack patterns. In general, overseer units are stronger than normal guards. For the purpose of the combat difficulty curve understanding, civilians were not calculated. The stealth difficulty was calculated according to the number of total enemies in an area, the variety of their guarding patterns and the available covers. When the covers are conveniently placed the difficulty is lessened, whereas when the covers are in hard to reach places, difficulty is increased. Level 1: Name Combat Difficulty Stealth Difficulty The Mansion 2 2 The Streets 3 4 The Docs 4 3

Level 2: Name Combat Difficulty Stealth Difficulty First Hostile territory 2 2 Overseer Territory 4 3 Past the Railway 4 4

7.1.4 System Evaluation Process In the beginning, every different player that will take part in the evaluation process in the Dishonored 2 test-bed create their own player profile. During their playthrough, their stats will be calculated using the in-game datamining system. Their individual skill in each playstyle is constantly calculated and updated. According to the Hyelight system suggestion though, only after the players have completed an Area Cluster, do their skills affect the next Area’s difficulty.

7.1.5 Player Approach and Reward System To test the effectiveness of the reward system that depends on player choice instead of random/ predetermined rewards, players will be awarded depending on their preferred playstyle as described in the Hyelight process. The number of choices for every playstyle the player opted to is recorded in the in-game menu. According to the player stats, after the first level is completed, the player is rewarded according to their choice. If they preferred the Stealth playstyle, they get the supernatural benefit of being less easily perceived while standing above enemies. If they preferred the combat playstyle, they get the added benefit of intimidating personality, so enemies will only be able to attack them one at a time. Both of these rewards are given to the testers via out of game means, and are not used as rewards in the normal playthroughs.

7.2 SECOND SYSTEM TEST – PEN AND PAPER GAMES To push the boundaries of this theory to the edge, a campaign of pen and paper games was organized, to test the hypotheses in a non- digital environment. The game system used for this research was the d20 system by Wizards of the Coast. The game that was played was Dungeons and Dragons 3rd edition due to the players’ familiarity with the system.

7.2.1 Pen and Paper Games Pen and paper roleplaying games are games that can be played with a group of players (usually a minimum of three) as well as a game master. The Game master’s role is to create and narrate a story to the player group. Players perform actions depending on their character profiles and try to reach the end of the adventure. Each player controls a single character and every character has a set of abilities and special qualities. The game Is played using rulebooks containing all the available characters, classes and special abilities, as well as enemy encounters and challenges for the players to face. Players use dice to determine special skills and talk with each other to find solutions that will further their quests in the game world. Gaming sessions can last from a single night to years, depending on the campaign. When players test their skills a combination of their attribute scores and dice rolls is compared against each encounter. Harder encounters require either more players to group together to succeed, better dice rolls, higher attribute stats, better equipment or different planning. In pen and paper games players are free to do whatever they desire, making it an extreme case of a game with multiple gameplay elements. The total number of available playstyles is totally dependent on the Game Master.

7.2.2 Evaluation Participants For this evaluation seven different players were involved all playing in a single party. Six out of the seven players were veterans of the game, knowing the system in and out. The last participant was a new player with only a single small campaign completed thus far. Four of the seven participants have played in the same group multiple times and so, they have become accustomed to each other’s playstyle and nuances.

7.2.3 Evaluation Process Player Stress In pen and paper games, understanding player stress is an easy metric for various reasons. For one, when a player gets stressed, he makes it apparent by roleplaying less, or stops contributing in the game as much. Other players can understand each other’s stress and are usually affected by it. When the gaming group is stressed, immersion is lessened and more often than not, the session either stops or starts becoming unpleasant.

The playstyles tested during gameplay were three. The first is the competence of the group in “Combat Encounters”, this is dependent on a few variables:

• The number and strength of the enemies. It is understandable that the stronger the enemies, the harder the challenge, the most important aspect of this playstyle is that for harder difficulties the way the enemies prepare for combat is changed. When in the higher difficulty settings, enemies plan their encounters better and provide for a greater challenge. • The character level and abilities. For the purposes of this evaluation test, character levels and abilities remained the same during both playthroughs. • The group dynamic. When players prepare better for combat, they can get much greater advantages against their foes, by grouping together and planning appropriately, a few players can beat greater challenges than normal. Minimal group cooperation on the other hand can lead to players not being able to contest even relatively easier encounters.

The second playstyle judged was the “Social Interactions” players had through their characters with the in game Non-Player characters (NPCs). The criteria that made social interactions harder or easier are described below:

• NPC social skills. When the NPCs have higher social skill values they pose greater social threats to the players. • NPC initial approach. NPCs can be friendly, indifferent or even hostile when first meeting the player characters. This changes the way players can

continue on their quests dramatically. Players are required to make better calculated decisions and pay greater attention to their social skills. The third playstyle is “Adventuring” and the main values are as follows:

• Players have a variety of traversal abilities they can use to remain undetected, for a better challenge their enemies can become greater in spotting them. • When traveling in nature, characters have different abilities that allow for them to survive. Harsher weather conditions and scarcer food can become great obstacles for inexperienced groups. The evaluation process consisted of three steps: First Playthrough with preset difficulty The group played the quest once with the normal difficulty in all the gameplay features. All the variables in the game remained unchanged and the group played this specific quest for the first time. No one had played this quest before, so all the encounters and story elements were new. There was no player stressed caused from out- of game sources. Players seemed stressed in two distinct situations, one was when two combat encounters took place too soon the one after the other, the other was after a particularly difficulty social Interaction in a city with a lot of indifferent NPCs (where players struggled to find a way to be accepted to High Society and further out their quest). Since in pen and paper games player stress (all of its forms) are apparent to the Game Master, even though it was recorded no action was taken to relieve it via gameplay and encounters. Players were asked to keep notes to describe their experience during gameplay and include points where things felt too stressful or too simple. The first playthrough took a total of 6 hours and was concluded in two 3-hour sessions. Second Playthrough using the Hyelight System The group played through the same quest once more, this time with the TDDA system applied to it. The main quest consisted of three area clusters. Each Area cluster was created based on the quest’s fractal curves. Each fractal curve consisted of an easy first encounter followed by increasingly difficult challenges and concluded with a final hard part. It was paramount that after every hard or stressful part of the game, players would have a more relaxing experience so that stress could be relieved. Due to this being the second playthrough, all players knew all the story beforehand so there was less debate over certain locations and the validity of in-game information, the expectations for the second playthrough were that it would

79 conclude in a far shorter period of time. The total playthrough was a little over 5 hours long, considerably longer than initially expected. During the second playtest, player stress was apparent in two separate occasions, both of which were during Social Interaction encounters. The high stress points were discovered by paying close attention to the amount of roleplaying that players strived for. When players get more stressed, they usually stop actively roleplaying and pay less attention to thee in-game narrative. In the game’s final combat, some players that were not combat oriented seemed a little off put and bored. In order to relieve stress and cure boredom players were given short in-- game resting time. The resting periods consisted of three short narratives that players could explore about an NPCs background and the town’s history. During those periods of rest, players found out about certain aspects of the world as well as had time to get back into roleplaying and relax between or even during harder encounters.

7.2.4 Evaluation results After both playthroughs, players were individually asked to participate in open form interviews, where they could explain their experiences in both playthroughs, pick the one they preferred the most and analyze all the elements they found stressful or boring. Since the playthroughs are not made by an individual player, but rather by a full team of them, I collected all of the most important information gathered during those interviews, especially those mentioned by more than one player.

• The second playthrough was considered equally enjoyable to the first one, even if all of the group knew the main story beforehand. The two newest members of the group were less interested the second time since they played mostly for the narrative parts of the game. • 5 players found the game more immersive the second time. All 7 of the players found the social interactions much more engaging, even including a stressful event that occurred when they tried to get classified information about the location of an aristocrat by seducing his secretary. In the second playthrough, she was much harder to get close to and her social skills were increased. • In the Hyelight system playthrough the combat encounters played out for longer and the 4 players that were the main combatants described the experience as more engaging and even though it was much harder it felt fair. The group’s dynamic was more consistent during combat encounters the second time. They managed to communicate more clearly with each other because the enemies were harder to beat. If the TDDA system was not used and the team played the same combat encounters with the preset difficulty, it is believed that they would be less interested, or even have their interest levels drop to boredom. • The players that were not so combat oriented in their playstyles started becoming bored in the second playthrough where combat time was increased. For them, combat was not as engaging to begin with, so making

them wait through it would get very boring after a while. To compensate for that, the three of them were given the opportunity to use one of their abilities to delve into a character’s past mid- combat and play a short narrative experience. The result of this short break could help them and the rest of the team afterwards. During the interview, two of the players said that the short story helped them get back into character and did not let them get bored, while the third player argued that it did not help as much. • Players reported that the differences in the social encounters were not as apparent as those in the combat and traversal gameplay elements. The way social encounters work, there can be many different occasions where players socialize better because they feel immersed and roleplay more, and other occasions where even with better chances to beat social encounters they roleplay less and lose due to loss of concentration.

7.3 FINAL SYSTEM TEST – HYELIGHT GAME For the final test of the system, the newly created game was tested with different players. The procedure followed for each of the participants was identical in every way. The testing environment was the same and all the playtests took place in the same hours each day of testing. The procedure followed is described below:

7.3.1 Phase 1 - Pregame interview During the first phase of the evaluation process all participants were asked a few questions about their gaming background and areas of interest regarding gameplay features. They were also introduced to the steps that they would be taking in this evaluation and what was required of them. The questions posed to the testers were as follows: 1. What kind of gamer are you? Casual or Hardcore? Since the distinction between Casual and hardcore players is one that if not explained correctly, can lead to misinformation, the differences between these groups were first explained to the testers (Justin T. Alexander, 2013). A hardcore gamer is the player that enjoys a more constant stream of challenge and doesn’t give up easily, whereas a casual player is a person who prefers to play games for fun and in their eyes, a small challenge can go a long way. This question was posed in order to categorize players and compare their perceived skill level with the in-game difficulty choices they will make in the next step. 2. What types of games do you enjoy playing the most? Players were asked this question in order to understand if they preferred to play games with multiple gameplay elements or games with a singular available playstyle. The opinion on the difficulty provided by the Hyelight system of players

that enjoy playing games with the platforming or combat elements would be much more accurate considering their expertise in the same playstyles. 3. Name the two games you have spent the most time on as well as the two games that you enjoyed playing the most. This question was posed for three reasons. First reason, when players have extensive experience in similar playstyles, they are expected to perform better and their playthroughs are a good judge of the game’s overall quality. If players don’t usually play the same genre of games, it is going to be very interesting to see how they perform in the manual difficulty setting vs the TDDA difficulty setting. Second reason is that this metric can also be used to test the accuracy of the testers’ self-categorization as Casual or Hardcore players. Hardcore players tend to have played more hours of competitive or especially difficult games, whereas casual players tend to play mostly what they enjoy. The third and final reason is to compare whether they spend more hours in games they enjoy the most, or others.

7.3.2 Phase 2 - Controls tutorial In the second phase of the evaluation process, each player was asked to open the game and play the tutorial level. This level was created for the sole purpose of getting players accustomed to the game’s controls and mechanics. There are no metrics implemented in the tutorial level because data are not required at this point. The goal of the tutorial level was for testers to understand all the main mechanics of the game, from jumping and dodging to attacking and shielding. During this phase, they received guidance in all the gameplay features and were given tips on how to maximize their potential. The tutorial consisted of three main steps. First the player would get the grasp of the basic controls, such as dodging and attacking enemies in combat. For this, this first area of the tutorial was supplied with a first group of enemies and a large fighting area. The player had a respawn very close, so that they wouldn’t need to run a long way to reach their destination. At the end of the tutorial level, players were greeted by the last type of enemy in a relatively easier difficulty so they would understand how they worked with minimum stress. Secondly, there was the area where testers would learn how to aim their long-range fireball attack and understand how cannons work. For this purpose, a fountain was placed near the edge of the fighting area, where the player could test shooting fireballs to a static cannon a few meters down the level. Third, the tester would learn how to step and jump through platforms while avoiding cannon shots. This area consisted of a moving platform, five static platforms and two cannons. When the player climbed the first static platform, they would be awarded with a small heal, so they both understood the utility of the healing item as well as complete the jumps easier. Since there were two cannons aiming at the player, using the shield was of paramount importance. Once the player reached the largest

82 platform, they were prompted to jump and use their float ability to land at the end of the level. Without the float ability, the jump could not be completed, so they were obligated to learn how to use it as well.

7.3.3 Phase 3 – Manual difficulty playthrough Right after playing the tutorial, players went into the third phase of the evaluation. There was no break between the tutorial and the manual playthrough stages. To begin with, players were prompted to choose a difficulty level that they deemed appropriate to their skill level. The choices were three, “Easy”, “Medium” and “Hard” and there were no descriptions about what each of those meant, that was something for each tester to find out for themselves. This phase was implemented to see how each player would judge their skills in comparison to their self-assessment. Players with similar experiences in platforming or combat games based on stamina control were expected to choose harder difficulties, whereas more casual players or those without similar experiences were expected to try the less challenging choices. At this point, players had a vague idea of what the game was about and how it was played since they have already played the tutorial level and they were introduced to both playstyles as well as the available enemies. Testers were asked to reach the end of the level and choose their way in the process. There was no further guidance given during gameplay. They were asked not to talk during the sessions and concentrate into beating the game. It was explained that playing better meant dodging more enemy attacks, shielding cannon hits and getting hit by either to a minimum amount. They were required to have this piece of information so that they understood what “playing good” and what “playing bad” was supposed to be and so that the player modeling algorithm wouldn’t be cheated. The level testers were required to play consisted of five large platforming parts, five stronger enemy encounters and eight less difficult ones. Every difficulty level was created with a large difficulty curve that would start low and build up periodically before the last fight, by the temple. Enemies, platforms and cannons alike grew from easier to harder in a way that would be appropriate in a similar game with multiple gameplay elements. The difficulty choice of the tester affected all gameplay elements equally, when combat was harder, the platforming was harder. All elements of the game were slowly but steadily increasing in difficulty, slower paced areas affected all the gameplay features equally.

7.3.4 Phase 4 – Targeted dynamic difficulty Adjustment Playthrough After a ten-minute break to relieve stress and give the testers time to stretch their hands and have a glass of water, the next phase began. During this phase, testers were asked to once more play the level they already completed. They were not given any details about this playthrough, other than the directions to complete it. Players did not know that their first playthrough

83 corresponded to their difficulty choice, neither did they know that the second playthrough would change the difficulty dynamically. Both plays were to be experienced separately and so the players did not get additional information about either of them. The second stage was identical to the first one in enemy placement and general direction, although this time the player modeling algorithm generated the enemy and platforming encounters according to player skill. The level was divided into 3 Area Clusters. The 1st one, “The Way in” played the role of the introductory cluster with a preset difficulty of 3 in both Platforming and Combat. “The Ship” was the 2nd Cluster, where enemy spawns would be adapted according to the player modeling algorithm that judged the testers’ combat skill during the first cluster. Similarly, the platforming difficulty was adjusted by spawning different platforms, cannons and ledges inside the cluster, this time based on the calculations of the testers’ Platforming skill of the dataminer. “Ascension” was the final cluster of the game, where both platforming and combat were adjusted depending on the player skill calculated in Area Cluster 2 (each one according to each own metric, of course). When the level was completed, a screen with the player’s scores would pop up along with a thank you note. The scores explained how well the players completed the game and their appropriate difficulties per Area Cluster.

7.3.5 Phase 5 - Final Interview After both playthroughs have been completed, testers were thanked for their participation in this evaluation and were given a couple of minutes to relax. Then, they were asked a set of questions that they were expected to answer freely and in as much detail as they liked. It was an open – form interview, where interviewees were asked to explain certain parts of their experience in depth, and afterwards had time to get into detail about aspects of gameplay and feel they deemed of importance. The main inquiry consisted of three main questions. 1. What are your opinions on the boat ride in each of the playthroughs? The boat ride question is of importance for both playthroughs. The boat was placed in a specific part of the level, where the player is expected to be at the peak of their ability in either combat, platforming or both. The boat ride is a stress- relief mechanism, a chance for players to wonder around, see the stars and admire the view, or at least stop worrying about their stamina and health consumption for a little while. The opinion of the testers on the boat ride would clarify a couple things, first it would be an indication of whether players felt sufficiently or partly challenged, secondly, it would provide insight to whether this type of “break” can be implemented successfully between clusters.

2. Which parts did you find the most challenging in each gameplay? When did you feel the most stressed and the most bored? Testers were now prompted to explain which parts of the overall experience felt more challenging, providing valuable information to their stress level through the whole game. With data deriving from this question, the overall balance of the game could be judged as well as any points that were not created to be stress-inducing and have inadvertently been left in the level, could now be found. Players were also asked to explain during which parts of the gameplay they felt more or less immersed into the experience. The player immersion was ranked on a Linkert Scale from 1 to 5, with 1 being “extremely bored”, 3 being “in flow” and 5 being “Extremely stressed”.

3. Why did you choose the difficulty you chose? It was very important to understand the players’ self-categorization in the difficulty spectrum. This piece information could be combined with the Targeted Dynamic Difficulty that was perceived to be appropriate for them. In later steps, the fact that they made those choices and their actual feeling towards them could be discovered.

4. Which playthrough felt harder to beat? Why? It was required for the player to know which difficulty mode felt more challenging to them, since there could be a vast difference between true player skill and perceived player skill. They were asked to explain in depth their opinions and point out which gameplay features felt harder in each playthrough, thus giving information that would differentiate combat and platforming difficulty (if they believed such a difficulty gap existed). Finally, they were requested to give their opinion on the last part of both experiences, where they had to fight a final group of enemies along with a platforming part that would eventually lead them to their destination. These last steps in the game, should have been very accurately adapted to player skill, since they have been through 2 Area Clusters already.

5. Which of the playthroughs did you enjoy the most? Why? This question was posed so that the researcher could know if players preferred the system under design or the normal difficulty picking mechanism. Considering the TDDA system was played second, players were more skilled overall by this point, so the game should have been easier to beat, although since this was the second playthrough of the same level, players may have found it less engaging than the first one. Answers to this question would also differentiate between the different views that players would enjoy the overall difficulty balance of gameplay features or if they preferred an adjusted/ separate difficulty for each gameplay feature.

7.3.6 The role of the researcher During the Manual and Targeted Difficulty playthroughs, the researcher did a variety of tasks.

1. Noted the way testers played During the playthrough testers would show different kinds of gameplay behavior that the implemented datamining system could not record. Only by careful observation by the game’s designer could such behaviors be understood. Such behaviors could include from dying on purpose, to missing attacks because of in game bugs. All these behaviors were noted down to be used as data as well as to form the following interview better. 2. Noted points where testers seemed more stressed Only by observation can the researcher understand player frustration and accidental mistakes. The in-game player modeling algorithm did not have a metric for player stress or boredom, neither were physiological methods implemented to calculate stress. When players were under pressure they were prompted to say it out loud if they needed to. 3. Calculated the total time of playthroughs and breaks The calculation of the total time of gameplay and most importantly the difference between each playthrough could provide a variety of important information about the system under evaluation. Another task was that the researcher would schedule the breaks between playthroughs and wait for testers to relax before starting the TDDA playthrough.

4. Minimize the risks of design mistakes to the final evaluation If during gameplay specific unforeseen problems presented themselves, such as game bugs that prevented saving or trapped people in certain areas. The researcher would only talk to testers that played in a way that would prohibit the player modeling algorithm to work, telling them to avoid such behaviors without pointing out the correct way for them to play. Even though the game was thoroughly tested, there can always be some bugs that wouldn’t show in the final datamining. Those mistakes caused by the game itself were noted down to make the evaluation process easier by excluding them from the final comparison of the results. 5. Videotaped player behavior during gameplay Gameplay sessions were videotaped so that by re-watching them, the researcher could understand player stress more deeply, as well as points of boredom. The way testers moved, grinned or changed their facial features at certain points in the game could be one more metric for evaluating the system.

7.3.7 Results and analysis In the Individual tester analysis, I describe each interview and playthrough of every tester that was involved in the evaluation process. I include player answers to inquiries, player statistics and overall skill level, difficulty choice as well as notes that derived from watching them play. I later analyze each one of those testers, starting from their choices and extracting the essence of their interviews in regard to the game system. A small chart of the main values indicated form the datamining process, as well as the players report on their immersion at different areas. Reported immersion is calculated on a Linkert scale from 1 to 5, with 1 being extreme boredom, 3 being complete immersion and 5 being extreme stress.

7.4 SYSTEM DESIGN CONCLUSIONS Based on the evaluations’ results, several positive and negative conclusions came to be. Positive conclusions are the parts of the System Hypotheses that were supported, while negative conclusions provide a good ground on which further research and development should be based on. Negative Conclusions 1. The first cluster was very problematic. It helped the system understand player skills in both gameplay elements, but it made some of them get bored because it was too easy and others very stressed because it was too hard. The first cluster should behave in a different way than the rest, it needs to start off in a way

that calculates player skill without going over or under the limits of optimal player experience. 2. Players that do not want to be challenged and prefer their skill to play only a small role in the game’s difficulty, find the TDDA system a little too challenging. This is the reason the “mood choice” element of the system could be helpful for those people. But since it was not tested in this game, there needs to be more testing to make a final decision on its usability. There needs to be further testing on the players that prefer lower difficulties.

Positive Conclusions 1. All the players that performed adequately enough in a cluster, did not perform lower after that in the next one. All the results prove that the ranking system implemented worked correctly and thus, the evaluation testbed was created correctly. 2. Thanks to the evaluation, the directions on how to create proper fractal curves were composed and are included at the endo of chapter 5.2.2 “Difficulty Curves”. 3. The Targeted Dynamic Difficulty Adjustment system did not make any of the players feel like the world changed and “World Believability” was sustained. Even after dying multiple times, the platforming parts did not change, and enemies didn’t get weaker. It felt like the world was more believable and it did not break player immersion. 4. None of the experiences that felt the most immersive to the players themselves could exist in a context where all difficulties were designed to be parallel. All the testers enjoyed playing the game more when each gameplay element was tailored to their ability and needs. 5. The datamining process and the player modeling algorithm proved to be a success, calculating appropriate player skill in both platforming and combat encounters. Thanks to that, the game could adapt into an appropriate challenge level, following the difficulty path crafted by the game’s designers. Thanks to the algorithm’s success, designers can create appropriate fractal difficulty curves for their games and be sure that most players will be challenged equally. A better algorithm for more complex games can provide even greater depth to the designer’s toolkit. 6. Reported Player Immersion was much smoother and stable in the TDDA system in comparison to the manual difficulty choice. Players enjoyed it more than the difficulty choice as well. 7. When players did not know that dynamic difficulty was in place, they did not feel patronized by the game’s difficulty. The researcher concludes that in certain kinds of games, where immersion and gameplay enjoyment is of the utmost importance, the TDDA system can be applied without making players feel less about themselves or the victory they just achieved.

8 FINAL THOUGHTS

In the end of this extended research, certain aspects about the difficulty creation in games were made clearer and several conclusions were reached. I highlight the most important of those conclusions and their potential impact in the games industry.

8.1 CONCLUSIONS

1. The games industry is moving away from dynamic difficulty models. They are only used for certain roguelike or freemium games so that there is enough diversity and pressure during gameplay. Designers have opted for the use of difficulty models, trying harder and harder to convince their players to choose freely between all difficulties even though they mostly design with medium challenges in mind. In my mind, this is but a bog where the industry seems stuck. Designers that have understood that started creating custom difficulty modes so that players can create their own experience, although these are not the optimal tools for player immersion (since players rarely understand their own skill and challenge needs). I believe there is untapped potential in the wedlock between dynamic and choice difficulty systems. This research is but a small concept of what can be if we think out of the box.

2. It was proven that players enjoy the game much more when the difficulty corresponds to their individual skills and they seem to enjoy the game more when the difficulty changes for each playstyle independently, instead of as a whole. This can be a great addition to games that place player experience above all. The need to compare to each other is not always required. Games like Journey and Flower are but two examples where players don’t compare their achievements, but rather discuss their experience with each other. Not all games can have such communities though, so the Hyelight system would best be suited to games that deeply invest in player feel and not player rivalry.

3. The main difference of the Hyelight system when compared to the other two widely used methodologies of difficulty creation is the inclusion of the game’s natural environment as a metric for adaptation. As a system it can be much harder to include in a game’s design, but even parts of it can prove useful tools in a designer’s toolbelt. The world design and the say of level designers in the design process can create a new dynamic between the player and the environment and make the world feel more realistic.

4. In the bottom line, it is all a matter of Marketing. Players that do not enjoy dynamic difficulty games can actually enjoy games with an adaptive system if the game itself is marketed more as an experience instead of a competitive

installment. Players play a game and enjoy it regardless of whether they are judged or not. Games that are not competition centered, can benefit greatly from systems that adapt player difficulty if they market them correctly. Players need to expect an immersive experience, not an experience that will be ground to prove themselves better than their friends. Where one excels the other may fail and vice versa.

8.2 FUTURE RESEARCH There are several ways to further improve the Hyelight system. Most of them require more research in one or more fields so that they provide accurate results. 1. Combine the Hyelight system with procedural generation algorithms Even though the system can function well without it, it is a very intriguing concept to use procedural generation algorithms in order to create long immersive experiences. Without the need for the custom creation of hundreds of difficulties by the design team, the games using the system will be much faster to produce, while at the same time, retain a fresh look and feel throughout. 2. Research the Mood system Since there have been players that did not want to be challenged almost at all, as well as players that might not want to be challenged less than a certain point, there needs to be a working system to support both of those player categories. The mood system can play that exact role, the one that helps players adjust the range of challenge the game will through at them 3. Include player stress calculation If the player stress calculation can be included in the model, the reward system will work much more reliably. If the game will be able to understand player stress and boredom the adaptation algorithm will provide a larger array of available playthroughs, all more enjoyable than the ones available at this moment. 4. Test player – player interactions I would like to evaluate the behavior of players that have both completed the game and see what kind of conversation they would have. Would they walk about the “true” game, will they argue over which playthrough was the “intended” one or would they talk about their experience in a different manner? Will they compare their skills to each other or will they conclude that there is no competitive element included in the game’s design? 5. Adapt the system in multiplayer games There needs to be a thorough research to find if this system can adapt with one way or another to multiplayer games. Maybe by adapting difficulties in solo missions, matching players that are good and need a challenge against players that are excellent but prefer a more relaxed playthrough or even provide individual experiences to players depending on their stats.

9 APPENDIX

In the appendix section of this thesis, different parts of the evaluation are included. The final test’s individual tester results as well as the Hyelight game’s difficulty calculation algorithm are described in depth, along with the Hyelight game’s stills.

9.1 INDIVIDUAL TESTER RESULTS Tester Number 1 Preliminary interview

• Hardcore Player, but it depends on the game. In group games that are designed for fun, he behaves more casual and does not mind losing, whereas in games that are competitive in nature, he tends to play very calculative and carefully to avoid any loss. He enjoys a good challenge. • Strategy and Action games are his favorite gaming genres. Since he seemed to enjoy Action games a lot, the Hyelight game was expected to be easy for him to grasp mechanically, and in particular, the combat gameplay feature. • His favorite games were Assassins Creed and Lord of the Rings 3, both action games and one of them a game with multiple gameplay elements. The tester understands the difficulty choice option and is familiar with the equal adaptation methodology of modern games with multiple gameplay elements. • The games he played the most were Warcraft and Dota. Both of these games are extremely competitive in nature and both have multiple gameplay elements. The fact that the tester played so many hours in competitive games along with the fact that he spent significantly less time in games that he enjoyed the most, confirms his earlier comment on him being a hardcore player. Gameplay Analysis Manual playthrough

• His choice in difficulty was Medium. • During his first playthrough, he preferred to play mostly by the combat mechanics, and avoided platforms when he was given the chance. When playing the platforming parts, he seemed frustrated and did not perform well, scoring lower than 40% on the platforming part in both the first and second clusters. • The final enemy encounters proved to be a stress point for the tester, and he died multiple times before managing to beat the level. His performance against enemies if the TDDA system was implemented here, would have suggested for the enemy difficulty to be lowered, since the enemies at the 2nd cluster were at the appropriate difficulty. • His level-completion time was 54 minutes.

Adjusted Playthrough

• This time, the tester was more experienced and managed to beat the first area cluster with ease, scoring 69% in combat for the first Area cluster (so the second cluster’s combat difficulty would scale up to 4) and 46% in platforming (making the second cluster’s platforming part rank at a difficulty of 3 – less than the same platforming area was in the medium difficulty). • When encountered with the platforming riddle of the second cluster, the tester seemed more interested in beating it and tried many times to find a unique way to solve it. His score in platforming for the second area was 48%, an almost perfect score for an appropriate challenge level. • Combat-wise, the tester beat the second cluster with a 46% score, thus the third area spawned with a difficulty of 4 (one less than the difficulty of the medium difficulty choice). • His level- completion time was 32 minutes.

Final Interview

• He explained that in both the playthroughs, the boat - ride felt like an appropriate resting place right after a hard combat and platforming part. • The most challenging part in his opinion was the 1st playthroughs enemies at the temple, where he considered stopping the game due to frustration caused by dying over and over. The second most challenging point was the platforming experience at the third cluster in the first playthrough, where at times it felt unbeatable. Those same points were his highest stress inducing places in the game, while there were no stressful points in the second playthrough. He did not feel bored during any part of the testing. • He said that he chose the Medium difficulty because he felt it was the “Normal difficulty”, not too hard and not too easy. • The first playthrough was much harder to beat, since it was the first time in contact with the game’s mechanics. The enemies and the platforming felt much harder. The cannon placement was trickier and at times it felt impossible to beat. • He preferred the second playthrough even though it was easier, solely based on the fact that there was no frustration involved in this experience. He felt more relaxed and concentrated and the platforming especially proved to be an enjoyable playthrough. The traversal parts of the game were more immersive and the enemies at the end felt like an appropriate challenge.

Tester Statistics (Main values only)

Cluster Name Playthrough Combat Platforming Reported difficulty difficulty difficulty Immersion The Way in Medium 3 3 4 The Ship Medium 4 4 3 Ascension Medium 5 5 5 The Way in Adjusted 3 3 2 The Ship Adjusted 4 3 3 Ascension Adjusted 4- 4 4- 4 3

Conclusions 1. The tester was significantly more challenged during the first playthrough, but his preference of the second one (even though easier overall experience) along with the greater immersion created by the elimination of stress points in the platforming part of the game. 2. The player enjoyed platforming only in the second playthrough, where it was easier. The second time he played, he was immersed in the platforming gameplay feature, while the first time it was a cause of frustration. Combat on the other hand, was harder than platforming, but still felt appropriate to the player. This is a good first indication that players can be more interested in a gameplay mechanic if it is adjusted to their skill level rather than being challenged on all different mechanics on equal terms. He did not feel patronized that the platforming was easier, on the contrary it came to be a more positive experience. 3. The player’s initial choice of “Medium difficulty” was not appropriate to their skill level. That was an expected outcome, since the player did not have enough experience in the game yet to be able to make an informed decision. 4. The targeted dynamic difficulty adjustment system created a more appropriate difficulty curve for each gameplay element. The fact that the tester was more immersed in the experience, is both an indication that the true skill calculation was correct and that the adjustment of the difficulties was appropriate.

Tester Number 2 Preliminary interview

• She is a casual gamer, she often plays competitive games, but does not enjoy being too challenged. • Her favorite game genres are RPGs and Action.

• The games she has played the most are Lord of the Rings online and Tera. Both of these games are online multiplayer games, both include a variety of gameplay elements and are great for both relaxed and hard experiences. • The games she enjoyed the most were Dragon Age Inquisition and The Witcher 3. Both games are famous for their multitude of gameplay elements.

Gameplay Analysis Manual playthrough

• Her choice of difficulty was Medium • In her first playthrough, she handled the combat parts moderately well, but even though she lost multiple times, she did not appear to be stressed by combat but rather enjoy it. She scored lower than 40% in both the first and second clusters in combat (in the TDDA system the combat difficulty would have been adapted to 2 for the second cluster and probably 2 or 3 for the third cluster). • The platforming proved to be a pain point for the tester, she died repeatedly from the first cluster (18 deaths) to the last cluster (27 deaths) and seemed extremely frustrated. While still playing she mentioned that if this wasn’t a test, she would have stopped playing. • The last combat felt off- putting as well, the vast number of enemies along with the fact that they were harder than the ones fought before, seemed to frustrate the tester. • Level completion time was 1h 5 minutes.

Adjusted Playthrough

• After the break, the player seemed to be back in the mood to play the last part, so the gameplay started with her stress levels at a minimum. • Since the first playthrough, the tester seemed to have improved in the platforming aspects of the game, not significantly, but enough for it to play smoother. She died 7 times on the first cluster and 2 at the third. She seemed much more confident and less frustrated in the platforming parts of this playthrough. The platforming difficulty was calculated to 3, across all clusters, significantly easier than the manual picked difficulty. • Her behavior in combat was more refined and defensive maneuvers were better executed. She faced easier enemies overall (the two first clusters were both set in a difficulty of 3, while the last cluster was calculated to a difficulty of 4). The difficulty of both clusters 2 and 3 were adjusted to one rank lower than those in the medium difficulty. • Level completion time was 37 minutes.

Final Interview

• She found the boat – riding part a well-placed rest and an opportunity to appreciate the environmental detail. Up to that point, she was consistently pressured enough that she wasn’t able to appreciate the setting. • She chose the Medium difficulty because she believed it was the “normal one for her skill level”. She said that she wouldn’t choose the easy difficulty because it felt like that would lower her self- esteem about her skill level. It felt like the Medium difficulty was the easiest she could choose freely. • In her opinion, the most challenging parts were the first cluster and the platforming part to reach the temple in the first playthrough. She argued that she would have stopped playing the game after the first cluster because she was very stressed with the platforming encounter. Her most notable stress encounter in combat was at the temple in the first playthrough. • The most difficult playthrough was the first. She found that she couldn’t complete the platforming parts in her first run, causing a lot of frustration. The second run felt easier, especially the platforming pats. There were no complaints about the combat, except for the final encounter of the first level. In the first try, she mentioned that she felt like she had less of an impact in comparison to the next. • The playthrough she enjoyed the most was the second one. She found the platforming to be of appropriate difficulty and challenged her enough for it to be interesting for her to solve the puzzle, but at the same time not too challenging as to cause frustration. She found the combat encounter to as challenging as the first try, but it seemed more enjoyable this time. She mentioned that she was immersed for a much longer period of time during the second try.

Tester Statistics (Main values only)

Cluster Name Playthrough Combat Platforming Reported difficulty difficulty difficulty Immersion The Way in Medium 3 3 4 The Ship Medium 4 4 4 Ascension Medium 5 5 5 The Way in Adjusted 3 3 4 The Ship Adjusted 3 3 3 Ascension Adjusted 3- 4 3- 3 3

Conclusions 1. First off, the tester enjoyed the second playthrough more and reported being consistently in flow. Her skillset grew from one playthrough to the next, but even by the end of the second try, she wasn’t skilled enough to beat the last enemies in medium difficulty. It was proven that the difficulty choice she made was not the one she had more fun playing, even though it was the only real choice she considered she had available. 2. Even if she performed poorly in the first platforming phase, by the second playthrough, since the difficulty was easier, she was tempted into trying harder and in return felt more successful for beating the platforming puzzles. She did not get stressed with the TDDA system in place, while at the same time she got a chance to try a way of playing she was not familiar with and feel good about it too. 3. In the second playthrough, she reported being slightly stressed in the first cluster of the game, even though her skill in both combat and platforming were sufficient. That might be an indication that the first cluster in the TDDA system should have a relatively easier difficulty. 4. She performed with almost extreme consistency in both combat and platforming for the first two clusters. This proved that in both clusters her ideal difficulty would be a difficulty of 3 in both combat and platforming, but by the end of the third cluster her skill in combat improved faster than her skill in platforming- thus making her ideal playthrough have a difference in optimal difficulty between the two playstyles.

Tester Number 3 Preliminary interview

• Casual gamer. Mainly plays to have fun, but nonetheless enjoys challenges. • His favorite gaming genres are RPGs and platformer games. He enjoys narrative experiences, but he grew up playing platforming titles almost exclusively. • The games he played the most were the same as his favorite games: Pokemon and Borderlands 2, an RPG title and an action game with multiple gameplay elements. It was interesting to find a casual gamer who played the most what he enjoyed the most. Gameplay Analysis Manual playthrough

• The tester confidently chose the Hard difficulty setting. • While playing, he further challenged himself fighting mostly in melee combat and not utilizing all the available long-range fireball attacks.

• In the beginning, he seemed exceptionally good in the platforming part, very confident and even managed to find a new way to traverse, by combining the available mechanics. He did not seem daunted in the slightest even when he died repeatedly up to the third cluster. • In the second platforming part, he was flawless. • The second combat encounter seemed to tire him out, so he started being more careful and used more long-range attacks. • After a while in the third cluster, the tester mentioned he doesn’t have a lot of patience. • He tried multiple times to beat the last platforming part and he seemed more stressed after every try. When he reached the final combat, he was already exhausted. After many deaths in the final encounter, the tester quit the game because it felt too frustrating to continue playing it. • Level completion time was 46 minutes, but the player quit at the last part.

Adjusted Playthrough

• The player seemed less stressed after the break. • The player was much more confident and played the game more carefully. The level went through much faster. • He seemed to enjoy enemy encounters a lot more, and in the second part he even fought all of them at once, while also attacking a cannon in melee combat. • The combat encounters were much easier in the second playthrough (at least 1 rank lower in difficulty). • Level completion time was 28 minutes Final Interview

• He found the boat- ride extremely helpful in both playthrough. In the first playthrough he was more stressed, but to a point that he couldn’t relax only by the boat ride. He said that even though it was a bit of a break, it helped more in the second try, where he was less stressed. He mentioned he would have wanted more things to see while on the boat. • The most stress – inducing parts were the second cluster’s platforming and the third cluster’s combat and platforming parts. At the end, the stress built in the player was so much that he quit. He mentioned that after such a playthrough it would take at least a few hours before he could try the same level again. • The most difficult playthrough was the first one, but the difficulty was extreme for what the player wanted to try. • The most enjoyable was the second one. He said it felt more appropriate to fight the second level’s enemies as well as that the platforming was more

intricate and provided a good enough challenge for him to find the best ways to beat the cannons.

Tester Statistics (Main values only)

Cluster Name Playthrough Combat Platforming Reported difficulty difficulty difficulty Immersion The Way in Medium 3 3 3 The Ship Medium 4 4 4 Ascension Medium 5 5 5 The Way in Adjusted 3 3 2 The Ship Adjusted 4 3 3 Ascension Adjusted 2- 3 2- 3 3

Conclusions 1. When a player that cannot handle a certain type of difficulty chooses it, he prefers to stop playing than changing it back to a lower one. 2. Even when the player wanted to enjoy a challenge, he still preferred the TDDA system over an overall harder experience, because overall harder experiences feel more daunting when difficulty is applied to all aspects of the game equally. 3. The TDDA system made the game hard enough for the player to enjoy playing, while keeping him at a state of flow for a prolonged period of time. 4. The tester had just been through an extremely difficult playthrough when he started the 2nd run, so he got slightly bored by the first cluster of the game, passing through it easily.

Tester Number 4 Preliminary interview

• She is a casual gamer, she never plays competitive games and does not enjoy difficulty games at all. • Her preferred game genres are Platforming and MMOs. She grew up playing platforming games so she was expected to perform well at the platforming parts of Hyelight. • The games she has spent more hours on as well as her favorite games were Crash Bandicoot and Abe’s Exodus. Both of which are puzzle- platformer games.

Gameplay Analysis Manual playthrough

• She chose the Easy gameplay difficulty. This was a choice that seemed appropriate to her aforementioned challenge preferences. • She quickly managed to get the hang of the platforming, probably due to her experience with similar mechanics. • She was afraid to fight a lot in the beginning, but after seeing how easily the enemies would die in melee, she started to fight more often. • After a while she started fighting more than she did platforming, since it seemed like the faster choice. • She was very cautious, always taking her time to aim her ranged attacks. • At the third cluster, she seemed to find the combat extremely easy, and it may have made her get bored, because after a while she seemed uninterested. • The whole last cluster seemed to be too easy for her both in platforming and combat. • The duration of the playthrough was 23 minutes.

Adjusted Playthrough

• She began playing a little bit bored from the earlier experience and the break. • She managed to beat the combat encounters after some tries, but it was considerably more difficult this time. She scored 33% in combat on the first cluster, 45% in the second one and an astounding 70% in the third. That means that when she started playing, she was skilled 2 in combat, and by the time she finished she got better and managed a true skill of 3, a slight improvement, but an improvement none the less. • She understood the difference between the platforming parts of the first and second playthroughs, but she seemed to prefer the difficulties of the higher challenge in the platforming part, since they took a little more thought and planning. • The tester complained that the character walked slower than she would have wanted her to. • She completed the game in 30 minutes Final Interview

• She mentioned that she would enjoy the ride more if she had more things to do by then. It felt like the boat- ride dragged on for too long and it got boring. • The most stressful part for her was the first cluster in the second playthrough. She couldn’t play well enough in her opinion to deal with the enemies in that area. During the first try, she got more bored than stressed, and that boredom carried on to the second level.

• The most difficult playthrough was the second one, where enemies felt considerably harder, and the platforms as well. • She preferred the first playthrough, because she did not want to be challenged as much as she got challenged in the second one. She mentioned that she enjoyed combat way more in the first try, but platforming felt much more rewarding the second time. • She mentioned that she would have liked to be more challenged at the last combat, preferably with a boss encounter.

Tester Statistics (Main values only)

Cluster Name Playthrough Combat Platforming Reported difficulty difficulty difficulty Immersion The Way in Medium 1 1 3 The Ship Medium 2 2 2 Ascension Medium 3 3 2 The Way in Adjusted 3 3 5 The Ship Adjusted 2 3 2 Ascension Adjusted 2-3 3 3

Conclusions 1. The player did not enjoy the extra difficulty, even when it was calculated to her actual ability, especially in combat. 2. She was not immersed for prolonged periods of time in any of the playthroughs. The points of her immersion occurred when the first cluster was at its’ easiest because she started getting to know the game and the basic features. Since the last combat felt very immersive and she performed exceptionally well at it, she seemed to enjoy it more and would have even liked a more difficult challenge. 3. Even though combat was not her strong point, she managed to get better at it, that did not mean that she enjoyed the greater challenge in that specific gameplay element. She wanted the platforming parts to be harder from the beginning, since so was much more skilled at them and she tended to have a lot more fun playing them. A similar difficulty between combat and platforming would have made for a negative gameplay experience for players like her.

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9.2 DIFFICULTY CALCULATION ALGORITHM For clarification purposes, the difficulty calculation algorithm used in the game is included below. It needs to be clear that this is not by any means an optimal solution, but one that at least worked for the purposes of the test, and proved successful. public void CalculateDif(out int combatDifOfNext,out int platDifOfNext)

{ #region CombatCalculations

#region CombatFeel

float EnemyTotalDefended = dodgedHeavyEnemyHits + dodgedLightEnemyHits + shieldedEnemyHits; float EnemyTotalHits =(((enemyLightHits * 0.4f) + (enemyLargeHits * 0.6f)) * 2);

if (KilledEnemies > 5) {

float CombatFeelBase = EnemyTotalDefended / (EnemyTotalHits + 0.000001f); if (CombatFeelBase <= 0) { CombatFeelBase = 0; } if (CombatFeelBase < 0.2f) { combatFeel = 0; } else if (CombatFeelBase < 0.4f) { combatFeel = 5; } else if (CombatFeelBase < 0.6f) { combatFeel = 10; } else if (CombatFeelBase < 0.8f) { combatFeel = 15; } else if (CombatFeelBase < 0.9f) { combatFeel = 20; }

else if (CombatFeelBase < 1.0f) { combatFeel = 25; }

else if (CombatFeelBase < 1.4f) { combatFeel = 30; } else if (CombatFeelBase < 1.8f) { combatFeel = 35; } else if (CombatFeelBase < 2.0f) {

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combatFeel = 40; } else if (CombatFeelBase < 2.3f) { combatFeel = 45; } else if (CombatFeelBase < 2.6f) { combatFeel = 50; } else if (CombatFeelBase < 3.0f) { combatFeel = 55; } else { combatFeel = 60; } } else combatFeel = 20; print("CombatFeel"+combatFeel); #endregion

#region DeathsByEnemies DeathByEnemyScore=0; if (deathsByEnemy == 0) { DeathByEnemyScore = 30; } else if (deathsByEnemy < 2) { DeathByEnemyScore = 25; } else if (deathsByEnemy < 5) { DeathByEnemyScore = 20; } else if (deathsByEnemy < 8) { DeathByEnemyScore = 15; } else if (deathsByEnemy < 12) { DeathByEnemyScore = 15; } else if (deathsByEnemy < 0) { print("error deathsByEnemy<0"); } else { DeathByEnemyScore = 0; } print("DeathsByEnemyScore"+DeathByEnemyScore); #endregion #region Accuracy if (attacks != 0) { accuracy =(int)((attacksHit* 10 / attacks) ); } else { accuracy = 0; } print("Accuracy:" +accuracy);

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#endregion combatDifOfNext = 0; finalCalcCombat = combatFeel + DeathByEnemyScore + accuracy; print("Combat:" + finalCalcCombat); if (finalCalcCombat <= 10) { combatDifOfNext = CombatDificultyOfCluster - 2; if (combatDifOfNext < 1) { combatDifOfNext = 1; } } else if (finalCalcCombat < 40) { combatDifOfNext = CombatDificultyOfCluster - 1; if (combatDifOfNext < 1) { combatDifOfNext = 1; } } else if (finalCalcCombat <= 60) { combatDifOfNext = CombatDificultyOfCluster; } else if (finalCalcCombat <= 89) { combatDifOfNext = CombatDificultyOfCluster+1; if (combatDifOfNext > 6) { combatDifOfNext = 6; } } else if (finalCalcCombat >= 90) { combatDifOfNext = CombatDificultyOfCluster+2; if (combatDifOfNext > 6) { combatDifOfNext = 6; } } #endregion

#region PlatformCalculations

#region CanonScore CanonScore =0; if (deathsByCanons < 0) { print("ERROR deathsByCanon<0"); } else if (deathsByCanons == 0) { CanonScore = 20; } else if (deathsByCanons < 2) { CanonScore = 15; } else if (deathsByCanons < 5) { CanonScore = 10; } else if (deathsByCanons < 9) {

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CanonScore = 5; } else { CanonScore = 0; }

print("CanonScore"+CanonScore); #endregion

#region KillboxScore killBoxScore = 0; if (deathsByKillBox < 0) { print("ERROR deathsByKillBox <0"); } else if (deathsByKillBox == 0) { killBoxScore = 20; } else if (deathsByKillBox <= 2) { killBoxScore = 17; } else if (deathsByKillBox <= 4) { killBoxScore = 14; } else if (deathsByKillBox <= 7) { killBoxScore = 8; } else if (deathsByKillBox <= 10) { killBoxScore = 4; } else { killBoxScore = 0; }

print("KillboxScore"+killBoxScore);

#endregion

#region platformAbility platformAbility = 0; float platformDefence = ((shieldedCanonHits * 0.3f) + (dodgedCanonHits * 0.7f)) * 2;

float platformSkill = platformDefence / (canonHits + 0.0000001f); if (platformDefence > 5) { if (platformSkill < 0) { print("platformSkill<0,(platformDefence / canonHits"); platformAbility = 0; } else if (platformSkill < 0.2f) { platformAbility = 0; } else if (platformSkill < 0.4f) {

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platformAbility = 3; } else if (platformSkill < 0.6f) { platformAbility = 5; } else if (platformSkill < 0.8f) { platformAbility = 8; } else if (platformSkill < 0.9f) { platformAbility = 10; } else if (platformSkill < 1.0f) { platformAbility = 13; } else if (platformSkill < 1.4f) { platformAbility = 18; } else if (platformSkill < 1.8f) { platformAbility = 25; } else if (platformSkill < 2f) { platformAbility = 32; } else if (platformSkill < 2.3f) { platformAbility = 36; } else if (platformSkill < 2.6f) { platformAbility = 40; } else if (platformSkill < 3f) { platformAbility = 45; } else { platformAbility = 50; } } else { platformAbility = 10; } print("PlatformAbility"+platformAbility);

#endregion platDifOfNext = 1; finalCalcPlat = platformAbility + killBoxScore + CanonScore + accuracy; print("Platforming:"+finalCalcPlat); if (finalCalcPlat <= 10) { platDifOfNext=PlatformDificultyOfCluster - 2; if (finalCalcPlat < 1) { platDifOfNext = 1; }

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} else if (finalCalcPlat < 40) { platDifOfNext = PlatformDificultyOfCluster - 1; if (platDifOfNext < 1) { platDifOfNext = 1; } } else if (finalCalcPlat <= 60) { platDifOfNext = PlatformDificultyOfCluster; } else if (finalCalcPlat <= 89) { platDifOfNext = PlatformDificultyOfCluster + 1; if (platDifOfNext > 6) { platDifOfNext = 6; } } else if (finalCalcPlat >= 90) { platDifOfNext = PlatformDificultyOfCluster + 2; if (platDifOfNext > 6) { platDifOfNext = 6; } } #endregion }

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9.3 GAME STILLS

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Bethesda. (2011, November). The Elder Scrolls, Skyrim. Bethesda.

Bethesda. (2014, May). Watchdogs. Bethesda.

CD Project Red. (2007- 2014). The Witcher Series. CD Project Red.

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