Building Players: Revisiting Bartle’s Taxonomy of Players

SUBMITTED IN PARTIAL FULFILMENT FOR THE DEGREE OF MASTER OF SCIENCE

Thomas van Dam 10002918

MASTER INFORMATION STUDIES GAME STUDIES

FACULTY OF SCIENCE UNIVERSITY OF AMSTERDAM

August 24, 2015

!

1st Supervisor 2nd Supervisor Dr. ing. S.C.J. (Sander) Bakkes Dr. Frank Nack ISLA, UvA ISLA, UvA Building Players: Revisiting Bartle’s Taxonomy of Players

Thomas van Dam University of Amsterdam Graduate School of Informatics Science Park 904, Amsterdam [email protected]

ABSTRACT substantially since 1996, logically there are new ways to behave in games which the Bartle Taxonomy of Players is not In order to better classify single-player games by the tuned to. However, this does not mean that Bartle's model is behaviours they facilitate, we propose a player model based on without use. It has been shown that numerous different player Bartle’s Taxonomy of Players. Through use of a questionnaire models are closely related to Bartle’s model and that the we evaluated the performance of this model compared to approach he takes with this model has its merits [19]. As we Bartle’s model, but were unable to find strong evidence that will discuss in more detail in the background chapter these made the new model stand out. We also argued that creative models come with their own shortcomings. Most notably a player behaviour should be considered as a unique and separate lack for expressing creative behaviour in games, which we kind of behaviour. This notion was supported by the data, as believe is important enough to consider separately. So for this the creative behaviour served as a significant identifier for study we take Bartle’s Taxonomy of Players and modify it so sandbox style games. that it caters to a wider variety of games, including games that focus on creative behaviour. In addition, we will look whether Keywords creative behaviour in games is worth giving its own category. Player modelling, Bartle’s Taxonomy of Players, sandbox, So briefly put the main research questions for this study are: games • Can a new model differentiate between single-player games better than Bartle’s model? 1. INTRODUCTION • Is it worthwhile to consider creative behaviour in With the ever increasing pace at which new games are released games separately? it becomes more and more difficult to find games that we like to play. While the can help in finding new games that 2. BACKGROUND we might like, either through professional reviews or In order to better understand what we set out to do it is comments from other individuals, the information provided is important to consider the context of this research. We will first mostly a subjective view of how the game was experienced. look at player modelling in a broader sense, before diving into While genre classifications offer some guidance, there can still the specifics of Bartle’s Taxonomy of Players. We will then be a wide variety of games within a genre that might or might take a look at other existing player models and their relation to not appeal to one’s personal taste. By looking at the kinds of Bartle’s, before finally considering the position of creative behaviour that games facilitate and players can enjoy, it is in player modelling. possible to create a model that provides an objective base for reviewers and consumers to evaluate the games they play or 2.1. Player Modelling maybe want to play. This is known as player modelling, and its Player modelling is a research area that focuses on analysing uses go beyond simply finding fun new games to play, both for how players go about in playing the games that they play, and academic purposes as business purposes. The academic value then using this information for various ends [4,15,20]. In lies in its usefulness as a common ground for researchers to addition, there are multiple ways to go about player modelling base their ideas and theories on. This ensures that the parties [4]. In this thesis we will exclusively deal with constructing a involved in the academic discussion are on the same page model based on the behaviour of the player displayed within a game. However, instead of working from the game’s point of regarding the observations made on player behaviour. view to gain insight into the player, we use the model to Additionally, this means that researchers can focus more on classify games based on the kinds of behaviour that they their subject matter, rather than having to explicitly explain facilitate. So rather than gaining insight into the individual how they are interpreting displayed behaviour. For a business player as to modify the game for optimal enjoyment, we focus player modelling can be useful since they could use the model on a more general view of the game, looking at how multiple of a certain player to recommend new games to the player that players play the game to gain insight into the game. This dual facilitate behaviour in line with the gathered model. purpose of player models makes them very versatile, which is why it is used in game development [15,20] as well as game A common player model that has been referenced numerous analysis [6,19]. times and keeps generating interest is the Bartle Taxonomy of Players [19]. Perhaps the reason for this is that it was one of 2.2. Bartle’s Taxonomy of Players the earliest, or that it is one of the more simple models, but nevertheless it remains one of the most well known models out 2.2.1 The model and player types there [19]. Yet there has been a fair amount of criticism Barte’s Taxonomy of Players grew out of a long discussion about the reasons why players play MUDs. While summarising regarding Bartle’s model, including by Bartle himself, who the contents of this discussion Bartle saw a pattern emerging; claims that his taxonomy might be incomplete for other types most reasons for playing could be grouped up in four distinct of games besides MUDs [7]. Games have evolved quite new cards for Magic: The Gathering [16]. They use a cast of Figure 1: Bartle’s Taxonomy of Players three player types: Timmy, Johnny, and Spike, which roughly correspond to Bartle’s Socialisers, Explorers, and Achievers. In addition, they also allow for players to associate with multiple playing styles in varying degrees of intensity. A possible reason for not having a Killer equivalent in the model Wizards of the Coast employ might be that the multiplayer aspect of the game is in most cases mutual. Players agree to play a game with each other, whereas in MUDs the players are placed in a game with random other players. 2.2.3 Shortcomings of Bartle’s Taxonomy In a world where new games and game genres pop up on a regular basis, the fact that Bartle’s model is twenty years old does not do it any favours. Since then games have moved at a breakneck speed, introducing various new ways to enjoy games along the way. Bartle’s Taxonomy is simply not equipped to classify behaviour in most modern games, categories [6]. This formed the base for his taxonomy, which although this does not mean the model itself is flawed. It is just can be observed in Figure 1. that when an industry develops so rapidly a twenty year old Bartle constructed two axes to map his four categories to, model can hardly be expected to have the same relevance. based on the sources of interest that each category has in the Which brings us to another shortcoming of Bartle’s Taxonomy game. On the x-axis there is a focus on players on the left, of Players; that it was initially designed for MUDs only, a quite versus a focus on the game world on the right. The y-axis goes specific kind of game which was popular at that time. This has from a focus on acting at the top, to a focus on interacting on made it difficult to use the model in different games, even the bottom. The player types are situated in the quadrants Massive Multiplayer Online Role-Playing Games, which share associated with their interests. A closer look at each of the many similarities with MUDs [7]. This greatly reduces the player types follows effectiveness of the model, especially when considering the 1) Achievers fact that MUDs (and MMO’s in general) are steadily declining in popularity [8]. Achievers focus on acting on the game world, which boils down to doing things in the game. They care little about the Pigeonholing Bartle’s model even further is the fact that it was other players in the game, or about the intricacies of the game developed based on an online multiplayer game. This means if it does not result in them gaining more points. that all games which focus more on delivering a single player experience are hard to classify using Bartle’s model. 2) Explorers Explorers are interesting in interacting with the game world, 2.3. Other Player Models always looking for new things in the game. They thrive on Up to now we have almost exclusively dealt with Bartle’s being surprised by the game, but not so much by other players. Taxonomy of Players, but there are numerous other models out 3) Socialisers there that aim to categorise players by their playing style. A particularly interesting model is the Four Keirsy Temperaments As the name suggests, socialisers focus on interacting with [13], which uses a categorisation very similar to Bartle’s. other players. They want to get to know new players and These were not derived from people playing games, but rather engage in social activity with them. For them, the game world a pattern Keirsey observed from the sixteen types of the is mostly a backdrop to their social engagements. Myers-Briggs personality model. These four categories are 4) Killers high level constructs of personality traits, which can be seen as Killers are looking to impose themselves on others, acting on a superset of Bartle’s player types [19]. Even though Keirsey’s players rather than the game world. They thrive on Temperaments are not specifically tailored to games, they do demonstrating how superior they are to other individuals, allow for categorisation based on the type of behaviour a merely beating computerised opponents is not enough for person exhibits in the world, or in a game world [19]. them. Another four type model is the model constructed by Bateman, the Demographic model (DGD1) [9]. Through 2.2.2 Strengths of Bartle’s Taxonomy observation of video games Bateman came to four player types Perhaps one of the biggest strengths of Bartle’s model is its that are all slightly different from the four Bartle types. relative simplicity. With just four player types, divided over However, as Stewart notes, it is possible to construe the types two distinct axes it is easy to comprehend and intuitive to use. of the DGD1 model as hybrids of the Bartle types [19]. By Additionally, the use of a scale allows for player models to elaborating on the Hardcore and Casual modes described by have varying degrees of interest in the aspects of the game. A Bateman, Stewart created six types that function as all possible player is usually not limited to one style of play, and can hybrid combinations of the Bartle types. dabble in other styles from time to time. Bartle can account for this by assigning values to each of the axes for a player, This brings us to the Unified Model, which is the brainchild of creating a multi-dimensional model rather than just a single Stewart [19]. In this model he incorporates many different player type. player models, as we already touched upon in the previous paragraphs. He shows that a number of the most well-known The fact that classifications similar to that of Bartle are player models as well as game design models share so many widespread also adds merit to quality of this type of conceptual elements that it is possible to combine them all in a classification. As Stewart notes, a great deal of player models single model [19]. are very similar to Bartle, and thus to one another [19]. Further on in this thesis we will take a closer look at these other 2.4. Sandbox Games models. In addition to scientific player models, there are also In all the different aforementioned models we observed that industry examples of companies that use a classification which most did not explicitly deal with the creative aspect that some shares similarities with Bartle’s model. Most notably is the players enjoy in video games. The popularity of sandbox model employed by Wizards of the Coast in their design of games such as shows that there is a desire for games with no explicit purpose other than to build or create whatever 3.1.2 Vertical axis the player desires. Most models regarded building as a The vertical axis is exactly the same as it is in Bartle’s model, component of simulation, where the player wants to copy since we felt that the distinction Bartle [6] makes between something from the real world. While the unified model does acting on the game world and interacting with the game world consider creative building, it is shoehorned into Bartle’s is also present in single player games. explorer category [19]. Research has shown that sandbox players are motivated by a unique set of motivators that are not 3.2. ACE2 Types reflected in any existing player model [10,21]. We believe that We will now describe all four player types, which the model the sandbox aspect of games should be seen as its own derives its name from (Achievers, Creators, Explorers, category. Engagers), in detail and highlight the kinds of gameplay that they enjoy. 3. A.C.E2, A NEW MODEL To address the shortcomings in Bartle’s model we took his 1) Achievers model and made some adjustments to it in order to make it The achievers in this model are very similar to the achievers in applicable for a wider variety of games rather than just the Bartle’s model, since they focus on acting on the game MUDs from Bartle’s model. We will first look at how the axes mechanics, which is almost the same as Bartle’s acting on the changed in the model compared to Bartle’s model, and then game world. Achievers enjoy winning and gaining points, but proceed to look at the new player types in more detail. also enjoy obtaining mastery over the mechanics of the game. 3.1. Model Overview 2) Explorers While the explorers in this model share some traits with the explorers in Bartle’s model, they are more distinct than the Figure 2: A.C.E2 achievers. They also seek to learn about the game’s intricacies and quirks, but more focused on the gameplay side. Exploring terrain is not as interesting to them as it is to Bartle’s explorers. They will often look for interesting interactions in games, such as unique combo’s in deck building games such as Hearthstone or novel use of . An example of the latter is ‘snaking’ in Kart DS, a technique that uses the drifting mechanic, which was intended for taking corners, to increase the speed of the vehicle on straight sections of the track as well. 3) Engagers Engagers are the first completely new type, and focus on interacting with the aesthetics of the game. They are more interested in the story or views a game provides, and not so much the gameplay. They will often look for games that trigger an emotional response, or that allows them to form an emotional bond with the characters in the game. Interactive Figure 2 shows the axes and player types in the ACE2 model. novels are an example of games that lean heavily towards this Straight away we can see that it is very reminiscent of Bartle’s category, as they oftentimes provide minimal gameplay but Taxonomy of Players. It also uses two axes and four player instead deliver a rich aesthetic experience. types. Below we discuss the motivation for both of the axes. 4) Creators 3.1.1 Horizontal axis Creators are the final player type in this model, and are also the As observed earlier, part of the weakness of Bartle’s model lies type that sets it apart from most other models. While this kind in the fact that it is geared towards a very specific kind of of behaviour is often a minor part of a different category, or game: MUDs. Since we wanted to create a model that was even completely disregarded, here it has its own player type. applicable to a wider variety of games we took a more abstract Creators, like engagers, are drawn towards the aesthetics of a approach to games. However, we quickly discovered that the game, but seek to act on them rather than interact with them. multiplayer aspect of games adds so many intricacies to the This manifests as creating structures or visuals within the kinds of behaviour that players display that we decided to limit game, effectively using the game as a creative outlet. Creators this model to single-player games. While this seems can also use the game to create their own aesthetic experience detrimental, it allowed for a greater degree of nuance than what as to trigger an emotional response in others who experience would have been possible had we included all kinds of games. their work. This includes creating levels that may elicit certain Since Bartle’s x-axis dealt with the distinction between the feelings from the player. and its player inhabitants, we were no longer able to use this axis. Instead we came up an axis that deals with 4. METHOD different ways of enjoying games. There are numerous reasons In order to examine how ACE2 held up compared to Bartle’s why players enjoy playing games [2,14], but that these can be taxonomy of players, we constructed a questionnaire in which divided into two main categories which we labeled Aesthetics participants were asked to rate how strong the focus on a and Mechanics. Whilst the term Aesthetics might be somewhat particular kind of behaviour was in selected games. By looking confusing due to its use in the MDA model [12], we felt that it at how the focuses are divided for both models we were able to best conveyed what we meant by it. Namely, the elements of compare the performance for the models on the selected the game that do not belong to the gameplay. This includes the games. We shall first discuss what games were selected for this narrative of a game, its visual style (or lack thereof) [18], the questionnaire, and subsequently discuss how the items of the soundtrack, but also the emotional responses that can be questionnaire were constructed. Finally, we shall discuss triggered by the game, which is why we decided to keep the briefly how the questionnaire was presented to the participants. reference to the MDA model. On the other side of the scale we have the Mechanics, which are the elements of the game that 4.1. Selected Games comprise the gameplay of a game. To ensure a wide variety of games we created a list of at least reasonably well-known games from many different genres. Game genres are still a quite active topic of debate in the 4.1.2.2 Adventure games scientific community, despite the fact that the notion has been Sam & Max is an early that has recently seen a around for many years now [1]. There have been many reboot. The focus on narrative and exploring the game world categorisations by many researchers [5,11,17], but we believe make it easily identifiable as an adventure game. Any of the that the genres put forward by Bakkes and the inclusion of one recent episodes is valid: Sam & Max Save the World, Sam & more encompass most games [3]. Below we will briefly Max Beyond Time and Space, Sam & Max: The Devil's discuss the genres as listed by Bakkes and finally the games Playhouse. selected for each genre. Similar to Sam & Max, Tales of is an early 4.1.1 Game genres adventure game that was rebooted not too long ago. Any of the Action: Action games mostly challenge the reaction speed of following episodes is considered valid: Launch of the their players. It is one of the most basic genres, with gameplay Screaming Narwhal, The Siege of Spinner Cay, Lair of the often emphasising combat. Leviathan, The Trial and Execution of , Rise of the Pirate God. Adventure: Adventure games focus on the narrative provided by the game, and often require the player to explore the game The Walking Dead: The Game is an original adventure game world and interact with the game characters. based on the television series of The Walking Dead, in turn based on the comic book series of the same name. It is an Role-playing: Role-playing games (RPGs) usually also focus interactive story game, with branching dialogue options and on a narrative in the game, but they differentiate themselves by multiple endings depending on the decisions of the player. Any letting the player take the role of a character that evolves over of the episodes in season 1 and 2 are valid. Season 1: A New the course of the game. Day, Starved for Help, Long Road Ahead, Around Every Simulation: Simulation games aim to mimic the real world, or Corner, No Time Left, 400 Days. Season 2: All That Remains, A sometimes a fictional world. They value relative realism House Divided, In Harm's Way, Amid the Ruins, No Going highly. Back. Strategy: Strategy games challenge the decision making 4.1.2.3 Role-playing games capabilities of the player. Where action games test the physical Baldur’s Gate is a classic role-playing game that is based on capabilities of the player, strategy games test the mental the tabletop RPG Dungeons and Dragons. Very little changed capabilities. Most strategy games seek to keep the role of between iterations and the remakes, so all the following titles chance to a minimum. are valid: Baldur's Gate, Baldur's Gate II, or their Enhanced Sandbox: This is the genre we added to the list put forward by editions. Bakkes [3]. As we observed in our evaluation of player Pokémon, aside from being a worldwide phenomenon, is also a models, the is a unique type that comes with its longstanding series or RPG games. Players take their own motivators and play styles. Without this genre certain characters through and adventure, and along the way the games become difficult to classify. While it is true that many characters grow and (literally) evolve. Over the years the core sandbox games add elements from other genres, mostly to gameplay has changed very little, sometimes to the dismay of appeal to players that pertain to different player categories, the critics, so all main games are considered valid for this study: differences are substantial enough to warrant a separate genre. Red, Blue, Yellow, Gold, Silver, Crystal, Ruby, Sapphire, The key feature of a sandbox game is that it does not provide Emerald, FireRed, LeafGreen, Diamond, Pearl, Platinum, the player with a goal to accomplish, which is almost always HeartGold, Soulsilver, Black, White, Black 2, White 2, X, Y, the case in other genres. A sandbox game is about the goals the Omega Ruby, Omega Sapphire. players set for themselves, which is why a pure sandbox game attracts a specific kind of player [21]. Final Fantasy is another longstanding series from Japan, with most games emphasising narrative. However, the gameplay 4.1.2 Selected games differs substantially between certain titles in the series, so for For each genre we selected three games in an attempt to cover this study only the following Final Fantasy games are as many of the sub-genres as possible. Some of the selected considered valid: VII, VIII, IX, X, X-2, XII, XIII, XIII-2, games were part of a series in which multiple games were Lightning Returns: Final Fantasy XIII. nearly identical in terms of the gameplay they provided. In such cases all these games were grouped under the series. 4.1.2.4 Simulation games Sim City is a popular simulation game, that has also seen some 4.1.2.1 Action games use in educational context. It aims to simulate the planning and Possibly one of the most iconic characters in the game development of a city, with the player acting as a supreme industry, Mario has spawned many different kinds of games. A entity pulling the strings. Sim City 2000 and Sim City 3000 are popular series of action platformer games is the similar enough for the purpose of this study. Bros. series. Since the core gameplay is very similar between Euro Truck Simulator places the player in the role of a truck all instalments, all are considered valid: Super Mario Bros., driver in Europe. As the name suggests, it simulates driving Super Mario Bros. 2, Super Mario Bros. 3, New Super Mario cargo from one place to another in a truck. Both Euro Truck Bros, New Super Mario Bros. 2, New Super Mario Bros. , Simulator and Euro Truck Simulator 2 are valid. New Super Mario Bros. U. is a more . It simulates the Street Fighter IV is the most recent instalment of the Street keeping of a dog or cat, with which the player can interact Fighter series. As the name suggests, it is a , through various means. While there are many games in this requiring quick reflexes and precision timing from the player. series, they are all so similar that they are all considered valid. Since IV introduces some new features, this is the only Nintendogs: Dachshund & Friends, Lab & Friends, instalment that is valid. Chihuahua & Friends. Nintendogs: Best Friends, Dalmatian & Halo is a franchise of mostly first-person shooter games, also a Friends. Nintendogs + Cats: French Bulldog & New Friends, staple of the action genre. While the multiplayer component of Golden Retriever & New Friends, Toy Poodle & New Friends. this game is often considered more important, it features an elaborate single-player component. Due to some new elements 4.1.2.5 Strategy games introduced in the game, only Halo III and Halo IV are Civilization is a long running series of turn-based strategy considered valid. games. The turn-based nature allows for players to think through their strategies carefully, whilst the game provides many different routes to victory. Due to the similar nature, both game, whereas A5 reflects the desire to explore the depth of Civilization IV or Civilization V are valid. the game. These are the two main ways in which players find StarCraft is also a long running series, but these are real-time out as much as they can about the game according to Bartle strategy games. This puts some more emphasis on the physical [6]. reaction speed of the player compared to the Civilization 4.2.1.3 Bartle's Socialisers series. Little has changed gameplay wise between the games, A8 and A9 were constructed for Bartle’s socialisers. In his so StarCraft, with or without the expansion Brood War, taxonomy, socialisers are predominantly concerned with their StarCraft II; Wings of Liberty, and StarCraft II: Heart of the social status (A9) and engaging in social activity (A8). Swarm are all valid. Last in the strategy genre is Portal, a puzzle game with some 4.2.1.4 Bartle's Killers focus on narrative as well. Whilst it may not be the purest Lastly, for Bartle’s killers we constructed A10 and A11. This puzzle game, it is one that became quite popular, which is category was the hardest to construct items for, since their unusual for puzzle games. Since the two are so similar, both main interest in the game is to cause distress in other players Portal and Portal 2 are valid. (A10). However, Bartle briefly mentions that sometimes the imposition upon others does not have to be detrimental for the 4.1.2.6 Sandbox games other player, and in cases killers might forcefully help Minecraft is possibly one of the most well-known sandbox another player [6], which is why A11 was included. games, as it exploded in popularity since its release in 2011. It incorporates elements from other genres, but at its heart it is a 4.2.2 ACE2 types three-dimensional creative block builder where players can For the ACE2 types we spent a large quantity of time create whatever they want. observing various games, including but not limited to the list of games selected for the questionnaire. Most of these Garry’s Mod is a three-dimensional physics sandbox based on observations were in the form of YouTube “Let’s Plays” or the Half-Life 2 engine, but later made into a standalone game. footage of players streaming their gameplay. By keeping track It features no goals, but allows players to manipulate items and of the various kinds of behaviours that these players exhibited props in the virtual world. in all these games we were able to categorise all this in three is often described as a two-dimensional Minecraft, as items per ACE2 type. Since the Bartle achievers and explorers it shares many properties with the game. The game leans a bit share traits with the ACE2 achievers and explorers, they also more heavily on the elements it borrows from other genres, but reuse some of their items. This had the added benefit of ultimately there is no goal in the game towards which the keeping down the number of items for the participants. player is steered, other than the goals players set themselves. 4.2.2.1 ACE2’s Achievers 4.2. Questionnaire Items This category shares the most overlap with its Bartle All items in the questionnaire took the form of a question about equivalent, using both A1 and A2 in addition to A3. We felt how strong a focus was in the game in question, which the that another element of achievement in some games can come participant could answer on a five point Likert scale ranging from the mastery of the game, most notably in action puzzle from “Very Strong” to “Barely There”. In addition, participants games such as Tetris, but also games such as Super Meat Boy, could also answer “Not Applicable” should they feel the item which provide incredibly tough gameplay where part of the was not relevant to the game in question, or “Can’t enjoyment can come from mastering the mechanics of the Remember” should they be unable to remember whether said game. element was present in the game or not. 4.2.2.2 ACE2’s Explorers Included in Appendix A are all the questionnaire items as they Since exploring territories was a little too specific, we dropped were presented to the participants. The first line of each item A5 for the ACE2 explorers and only reused A4, in addition to contains the main statement, the proceeding lines contain a the new A6 and A7. A6 and A7 are very similar, since they more elaborate explanation. both deal with finding solutions to levels or problems. The For each Bartle type there are two items, and for each ACE2 difference lies in how the player goes about in doing it. A7 is type there are three items. We tried to balance this, but due to the most common form of play, where the player seeks to find the preciseness of Bartle’s types it proved impossible to come the best solution, whether it be using as few moves as possible up with additional items that were sufficiently unique. to complete a game or placing units for optimal gains in Likewise, we tried lowering the number of items for the ACE2 Civilization. A6 is more about finding unusual ways to model, but since we aimed to create more abstract types, accomplish a goal, for example using only a certain kind of having only two items was too limiting in covering the scope pokémon in a Pokémon game or creating a incredibly of each type. Below we shall discuss the items based on their convoluted solution in SpaceChem. associated player type, starting with the Bartle types. 4.2.2.3 ACE2’s Engagers 4.2.1 Bartle types For the ACE2 engagers we created items A12, A13, and A14. All the items for the Bartle types were constructed using Some players play games purely to enjoy the narrative that is Bartle’s original paper [6], by looking at which kinds of provided, sometimes caring very little for the gameplay itself. behaviour Bartle associated with each type. An example of this can be observed in the Warcraft games, which some players will play just to experience the story. 4.2.1.1 Bartle's Achievers Another way to engage with a game is in the visuals it For Bartle’s achievers we constructed items A1 and A2 provides, even though this sometimes comes at the cost of (Appendix A, item 1 and 2). According to Bartle, players that reduced gameplay. An example of a game that facilitates this seek to act on the world aim to beat various game goals and set behaviour is Monument Valley, where the main emphasis of the out to achieve them, which is reflected in A1. Oftentimes they game is on the Escher-like vistas. This is reflected in A13. look to increase some measure of their prowess, be it Lastly, some players seek to build ‘relations’ with the non- experience points or hoarding large amounts of currency. This player characters in a game. Dating simulation games are a is reflected in A2. prime example of games in which this behaviour is displayed, but it can also be observed in games such as Mass Effect and 4.2.1.2 Bartle's Explorers The Elder Scrolls. For Bartle’s explorers we constructed items A4 and A5. A4 is reflective of the explorers desire to explore the breadth of the 4.2.2.4 ACE2’s Creators which could be accessed by hovering over them with the Finally, for the ACE2 creators we constructed items A15, A16, mouse cursor. All items and their tooltips are included in and A17. A fair amount of modern games feature level creators Appendix A. as a way to increase the lifespan of the game. Some players After finishing the questionnaire the participant was shown one really enjoy this, and spend a great deal of their time with the of two screens, depending on whether they selected at least a game on creating new levels, which is reflected in A15. Level single game or none at all. We included these in Appendix E creation is featured in games like Worms, Super Meat Boy, and and Appendix F respectively. Participants could opt to leave Minecraft in the form of adventure maps. Minecraft can also their email address, stored separately from the questionnaire double as the virtual canvas for players to display their results, to be informed of the results upon completion of the architectural creations or pixel art, A16 reflects this kind of thesis. behaviour. Whilst less common, some games also allow for players to create their own narrative, either through creating a 4.4. Questionnaire Analysis custom level or campaign (Minecraft and Crashlanders) or When analysing the results we transformed the answers given through the creation of movie clips (machinima). Examples of by the participants into scores for each item. We subsequently the latter can be observed in the Rockstar Editor in GTA V, or combined these with items in the same category and took the the Halo scene creator. A17 reflects this kind of player average. In the case a participant answered “Can’t Remember” behaviour. we did not take this answer into account in the calculations. This gave us a score for every category for both models, which 4.2.3 Objectivity of the items we mapped on the plots shown below in Figures 3 and 4. The Since we constructed our own items for this questionnaire we scores range from 0 to 5, where 0 means that this player type is were very mindful of the fact that we could influence the not represented in the game at all according to the participants, results favourably for ACE2 just by how we chose the items. and 5 that this is one of the main foci of the game. To prevent this we took special care to focus on the actual behaviours we observed in gameplay footage, rather than on The reasoning behind this was that now games are identifiable what would best differentiate the new model from Bartle’s through their shape on the plot, as well as making for an easier model. visual comparison of differences between the models in the results. The visualisation is interactive and allows for a more 4.3. Questionnaire Procedure hands on approach in analysing the data. In addition, it makes Upon loading up the questionnaire the participant was greeted the gathered data more easily digestible by those who are with an introduction screen where the goal of the questionnaire interested in the results. was briefly explained, as well as explaining what was expected of the participant in their answering of the questions. In 5. RESULTS Appendix B we included a screen capture of the initial screen. First we will discuss how the models compare over all games., Special care was taken to ensure that the participants knew looking at the overall picture of the data. Second, we will take what was expected of them without guiding them too a closer look at each of the genres and how the model dealt explicitly. While the text does steer the participants towards a with them. certain answer, trial runs showed that without this explanation participants were confused by some of the items. Some of this 5.1. All Games confusion remained, but we will discuss this later. By calculating the average for all player types among all Upon starting the questionnaire the participant was presented games for both models we were able to create the plot that can with a screen in which they could select the games with which be observed in Figure 5 on the following page. The socialisers they felt comfortable enough to answer questions about. This and engagers, as well the killers and creators have been put on screen is included in Appendix C. the same ends of the axes in order to make comparison easier. While the two shapes are similar, the ACE2 model has three For every selected game the participant was asked to fill in the directions in which it expands, whereas Bartle’s model only form shown in Appendix A. In addition to the questions, the expands in two directions substantially. This indicates that screen also showed the games in question, and a small participants were able to categorise with a higher degree of reminder on how to judge certain questions. Again, whilst this nuance in ACE2, since more relevant options were available to seems to steer towards a certain result, trial runs showed that them. When looking at the data for all games separately rather people were confused with some items without the reminder, than averaged, this becomes clearer still, although the picture is and several testers recommended to add this paragraph. All a little messy. Appendix G1 plots the results for all games questions in the screen had additional info in their tooltips, individually using Bartle’s model. We observe that for Bartle’s

Figure 3: Bartle Axes Figure 4: A.C.E2 Axes Figure 5: Average All Games 5.2.2 Adventure games Appendix I1 plots the averages for adventure games for both models. The shapes for adventure games are very distinct when compared to other genres, for both Bartle’s model and the ACE2 model. All individual games were similar in shape to their average, so both models seem to be able to identify adventure games fairly smoothly. However, Bartle’s model only utilises two of the four axes, whereas ACE2 uses three. This allows for a higher degree of nuance in the categorisation of adventure games. 5.2.3 Role-playing games Appendix J1 plots the averages for Role-playing games for both models. Like adventure games, role-playing games all have similar shapes and are thus close to their average for both models. Bartle mainly utilises two of the axes, but it does not completely ignore the other two axes. The ACE2 model is again capable of showing more nuance by using three axes, but the creator axis is almost completely ignored. 5.2.4 Simulation games model that the killer and socialiser axes are sparsely populated Appendix K1 plots the data for simulation games for both with medium to low scores. Appendix G2 also plots the data models. Simulation games feature quite distinct shapes in both for the individual games, but using ACE2 instead. We see that models, although all scores across both models are on the the achiever, explorer, and engager axes are densely populated lower side. It seems that simulation games do not fit it quite as with high scores for the ACE2 model. While the creator axis is well as the other genres. also sparsely populated, the values on there reach higher scores, which suggests that for the games in which it was In appendix K2 and K3 we plot the individual games for Bartle relevant, it was highly so. and ACE2 respectively. Here we observe a similar situation to the action genre, except this time it is the ACE2 model that has 5.2. Genres a clear outlier game. We will come back to this in the findings Appendices H to M include the graphs for each of the six chapter. genres. We will go over them one by one, noting interesting 5.2.5 Strategy games differences between the two models or peculiar features of the Appendix L1 plots the data for strategy games for both models. models for that particular genre. When taking a look at the Bartle model for RPGs in Appendix 5.2.1 Action games J and strategy games in Appendix L1, we can clearly see that Appendix H1 plots the averages of the data for action games the two shapes are very similar. While the ACE2 model also for both models. We observe a slight difference between the has similarities, it scores lower on the engager axis and higher two models. Overall, the Bartle killers are more relevant for on the creator axis. action games than the ACE2 creators, but not significantly so p Appendix L2 and L3 plot the data for all strategy games < 0.07. individually for Bartle and ACE2. Here we observe that the However, things become more interesting when taking a look Bartle model has an outlier game that differs quite substantially at how the individual action games score in H2 for Bartle and from the average. H3 for ACE2. As one can see in H3, the graphs for the three 5.2.6 Sandbox games games are all fairly similar to the average in H1. This indicates Appendix M1 plots the averages of the data for the sandbox that the average is a fair representation of the three action games for both models. Sandbox games generate distinct games. Yet when looking at Bartle things are a little different. patterns in both models, making them easily identifiable. The All three games have distinct shapes, and none of them are Bartle model shows a little more variance in the individual close to the average in H1. It seems that the more low level games than ACE2, as can be observed in Figures 6 and 7, but nature of Bartle’s model is unable to generate a good abstract view of the action genre.

Figure 6: Sandbox Games in Bartle Figure 7: Sandbox Games in A.C.E2 overall the individual games are similar to the average in both Figure 9, where the three games feature have distinct shapes, models. allowing for simple and intuitive identification when observing When looking at the creators axis in the individual games the data. This shows us that while the differences might not be (Appendices H3-M3), we can see that with a single exception significant in a statistical sense, the models do offer some use all high scores are in the sandbox genre. The one exception is in creating intuitive comparisons that can help people in in simulation games, where the city builder Sim City also finding similarities and differences between games. scores high on the creators axis. The difference in scores on the creators axis for sandbox game and any other genre is 6.2. Study Limitations significant, with an unpaired t test giving a value of p < 0.04 Whilst the creator is quite solid as a player type, it does not fit for sandbox versus simulation, and p < 0.003 for sandbox perfectly in the model. It is located between Acting and versus other genres. Aesthetics, yet level creation is also considered as creator behaviour, even though this is quite possibly more related to 6. DISCUSSION mechanics than aesthetics. This shows that the model has clear limitations in the range of player behaviours it can model. In this chapter we will discuss our findings and reflect on the limitation of this study. The questionnaire featured three items per ACE2 category, whereas it only had two items for each Bartle category. 6.1. Findings Additionally, while creating the items a bias might have been When comparing the various axes with unpaired t tests across introduced, which would lead the results to be favourable for various genres we found very little significant differences, the ACE2 model. To combat this we were careful with steering even though by observing the graphs there seems to be a the answers too much when constructing the items of the substantial difference. An explanation for this is that it seems questionnaire. However, it was difficult finding the balance not all participants understood that the questionnaire was between ensuring the participants understood what was focused exclusively on single-player games and thus still used Bartle’s killers and socialisers, whilst one would assume that expected of them whilst making sure not to influence their these play no role in single-player games. However, the decisions too strongly. This partially explains the scores that creators type forms the exception to this, showing a overall the Killer and Socialiser category received. Considering the highly significant (p < 0.04) difference between the sandbox fact that the questionnaire dealt with single-player games, and genre and others. This supports our hypothesis that the creative these categories are very much multi-player oriented, we player is a unique kind of player that should be considered expected these to score lower than they did. separately from other player types. The number of respondents was limited, barely reaching forty Staying with the creative type, we want to briefly reflect on the filled in questionnaires. This meant that the less popular games ACE2 outlier in the simulation games, Sim City. Due to their nature, simulation games will often borrow elements from received very few responses, with the lowest game only having other game genres in order to create the best simulation. In the a single respondent. case of Sim City, which is a city builder type game, it is no surprise that the creator player type is strongly represented 7. CONLUSION whereas it is not in the other simulation games. The answers At the onset of this thesis we set out to create a model that for the items pertaining to the creator type for Sim City differ would perform better than Bartle’s model in differentiating significantly from those for the other two simulation games, between single-player video games, with a particular focus on Euro Truck Simulator and Nintendogs, with p < 0.0133. This sandbox style games. In the data we gathered through the strengthens our hypothesis that creative gameplay is worth questionnaire we managed find some evidence which indicates considering separately even further. that the new ACE2 model allows for a nuanced labelling of single-player games, and that even though creative behaviour Lastly, while none of the results were significant, we did find does not feature often, when it does it is a defining feature. that the ACE2 model made it easier to differentiate between However, the Bartle model performed better than we had genres by eye. When looking at Figure 8, the three shapes in expected, showing again that despite its shortcomings it is still Bartle’s model are nearly identical even though they belong to a usable model. We hope that this research has shown that very different genres. This is more accurately reflected in approaches to player modelling similar to Bartle’s are

Figure 8: Super Mario Bros., Sim Figure 9: Super Mario Bros., Sim City, and City, and Final Fantasy in Bartle Final Fantasy in the A.C.E2 model worthwhile pursuing, even though the model proposed in this International Conference on the Foundations of Digital thesis may not be the best way to do so. Games, (2012), 282-283. 8. FUTURE WORK 11. Fairclough, C., Fagan, M., MacNamee, B., Cunningham, P. The research presented in this thesis was mostly exploratory, so Research Directions of AI in Computer Games. future work should seek to solidify the observations made. Proceedings of the 12th Irish Conference on Artificial There are multiple ways to go about this, most notably by Intelligence & Cognitive Science, (2003), 333-344. conducting a more widespread survey with many more respondents. Additionally, using a broader selection of games 12. Hunicke, R., LeBlanc, M., Zubek, R. MDA: A Formal can also be of help in further testing the validity of the model Approach to Game Design and Game Research. proposed in this thesis. To test how well the model preforms in Proceedings of the AAAI Workshop on Challenges in Game classifying games based on the behaviours they facilitate, a AI, 4 (2004). study could be conducted that asks participants for a particular game they enjoy. Then, based on data gathered previously, the 13. Keirsey, D. Please Understand Me II. Prometheus model can recommend a new game based on the prominent Nemesis, (1998). values in the game named by the participant. The participant can then spend some time with the game, and rate their 14. Lazzaro, N. Why We Play Games: Four Keys to More appreciation of the game. This servers the dual purpose of Emotion Without Story. Game Developers Conference, testing out the model, as well as the assumption that players March (2004). like a certain kind of behaviour, which they look for in games. 15. Rohs, M. Preference-based Player Modelling for Future research in player modelling in general should aim to Civilization IV. (2007). encompass a wider variety of players and behaviour. It seems like using only four axes does not do justice to the variety of 16. Rosewater, M. Our Three Favorite Players: Timmy, ways in which people enjoy games. Perhaps introducing a new Johnny, and Spike. (2002). http://archive.wizards.com/ axis will help in allowing more precise classification. Magic/magazine/article.aspx?x=mtgcom/daily/mr11b 9. ACKNOWLEDGEMENTS 17. Schaeffer, J. A Gamut of Games. AI Magazine, 22-3 We would like to use this opportunity to thank Sander Bakkes (2001), 29-46. for his invaluable feedback and support as supervisor to this 18. Solarski, C. The Aesthetics of Game Art and Game Design. thesis.. In addition, we would like to thank everyone who took the time to participate in the questionnaire and/or spread the , (2013). word about it. Lastly, we would like to thank one particular http://www.gamasutra.com/view/feature/185676/ artist, whose DJsets have provided the background music for the_aesthetics_of_game_art_and_.php?print=1 the majority of the process: Nuno Dos Santos (https:// 19. Stewart, B. Personalities and Playstyles: A Unified Model. soundcloud.com/nunodossantos). Gamasutra, (2011). 10. REFERENCES http://www.gamasutra.com/view/feature/6474/ 1. Apperley, T. H. Genre and Game Studies: Toward a personality_and_play_styles_a_.php?print=1 Critical Approach to Genres. Simulation 20. Thue, D., Bulitko, V., Spetch, M., Wasylishen, E. Gaming, 37-1 (2006), 6-23. Interactive Storytelling: A Player Modelling Approach. 2. Avedon, E. M., Sutton-Smith, B. The Study Of Games. AIIDE, (2007), 43-48. John Wiley, (1979). 21. Webber, N. Controlling a Sandbox. Ctrl-Alt-Play: Essays 3. Bakkes, S. C. J. Rapid Adaptation of Video Game AI. PhD on Control in Video Gaming. McFarland, (2013), 59-71. disseration, Universiteit van Tilburg, (2010). 4. Bakkes, S. C. J., Spronck, P. H. M., Lankeveld, G. Player Behavioural Modelling for Video Games. Entertainment Computing, 3 (2012), 71-79. 5. Bakkes, S. C. J., Spronck, P. H. M., Postma, E. O. Best- response Leaning of Team Behaviour in Quake III. Proceedings of the IJCAI 2005 Workshop on Reasoning, Representation, and Learning in Computer Games, (2005), 13-18. 6. Bartle, R. Hearts, Clubs, Diamonds, Spades: Players Who Suit MUDs. (1996). http://mud.co.uk/richard/hcds.htm 7. Bartle, R. Player Type Theory: Uses and Abuses. Casual Connect. (2012). https://www.youtube.com/watch? v=ZIzLbE-93nc 8. Bartle, R. The Decline of MMOs. (2013). http://mud.co.uk/ richard/The%20Decline%20of%20MMOs.pdf 9. Bateman, C. 21st Century Game Design. Charles River Media, (2005). 10. Canossa, A. Give Me A Reason To Dig: Qualitative Associations Between Player Behaviour Found in Minecraft and Life Motives. Proceedings of the Appendix A

All statements were prefaced with “How strong is the focus on…”

— Achievers 1. Winning. Beating levels or opponents in the game. 2. Gaining points. Increasing a value, be it experience points, gold, achievement points, or anything similar. 3. Mastering the game. Getting better and better at the game. The learning curve is a large part of the game.

— Explorers 4. Finding interaction between game elements. Discovering how game elements interact with each other, finding the limits of the . 5. Finding unexplored territories. Discovering areas in the game that few other players have been to. 6. Finding alternate strategies. Beating levels in different ways than what is most obvious; finding new ways to accomplish something. 7. Finding the optimal solution or setup. Finding the optimal solution for a puzzle, or finding equipment/weapon combination that provide the best stat boosts.

— Socialisers 8. Getting to know new players. Meeting new players and communicating with them to get know them better. 9. Improving your social status in the community. Getting more players to know you and see you in a positive light.

— Killers 10. Causing distress in other players. Interacting with other players in the game world as to ruin their day. Often by killing their in game character. 11. Imposing yourself on other players. (Forcefully) interacting with other players in the game world.

— Engagers 12. Experiencing the narrative of the game. The game features an extensive story. 13. Experiencing the visuals of the game. The game provides stunning views, or features a particular art style. 14. Interacting with the Non-player Characters of the game. Engaging in dialogue with computer controlled characters, or in other ways interacting with them.

— Creators 15. Creating new levels. Constructing new levels that are playable by others. 16. Creating your own structures, landscapes, or visuals. Using the game as a creative outlet. An example of visuals would be pixel art. 17. Creating your own narrative. Creating your own story for a custom campaign, or using the game to create a movie (machinima). Appendix B Appendix C Appendix D Appendix E Appendix F

Appendix G

All games.

1. 2. Appendix H

Action games.

1.

2. 3. Appendix I

Adventure games.

1. Appendix J

Role-playing games. Appendix K

Simulation games.

2. 3. Appendix L

Strategy games.

1.

2. 3. Appendix M

Sandbox games.

1.