DOCSLIB.ORG

Mike and Phil's Pocket Games

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mike and Phil's Pocket Games Mike and Phil’s pocket games No Prop Human Rock Paper Scissors – The group is split into 2 teams and they will be shown the “proper” Rock, Paper, and Scissor positions. For rock the group is to drop low to the ground and try and make themselves “ball like”. For paper, you will stand as tall as you can with your legs spread apart and arms reaching up and out as high as you can resembling the letter “X”. For paper you will reach your arms straight out in front of you and clap your hands and arms together, resembling the “Gator Chop” (BOOOOOOO!!!!). The 2 teams will have 1 minute to huddle and come up with a position that they will portray 1st with 2 back ups in case of a tie. Both teams will stand at the center of the field on opposite sides of the mid line. On the count of “rock, paper, scissors, shoot” the teams will demonstrate their symbol. Whichever team wins will then try and tag as many of the opposing teams players as possible before the successfully cross the end line behind them which is located about 20-25 feet from the center line. Any player that is tagged before they cross the line will become a part of the other team. In cases where a tie is reached then the teams will “recount” and use their 2nd choice and 3rd if necessary. If all 3 rounds end in a tie then the teams will re-huddle and come up with 3 new options. The game ends when all players are on 1 team. All players on each team must show the same sign at the line. Giants Wizards and Elves - This game is played just like human rock paper scissors only the positions are different. A giant is portrayed by standing straight upright with your hands extended directly above your head as high as you can reach. The Wizard is shown by extending one arm out in front casting a spell and the elves is shown by squatting down low to the ground. Giants beat wizards, wizards beat elves and elves beat giants. Same You’re Outta the Game / Tie-U-Die Number of players: Any number Equipment needed: None Activity time: 7-10 minutes How to play: This is a clever variation to the Rock, Scissors, Paper game. In "Same You’re Outta the Game," players play until there is only one player left in the group. To begin, have all participants get a partner. Play using basic RSP rules. Have all participants with their partners turn back-to-back and on 3 they turn around and display one of the above signs. If you lose, you sit-down. If you win, you go and find another player that has won and will challenge them. If, at any time, two players "Tie" (do the same sign), they both die and are out of the game. Variation: Instead of RPS, you can use the following signs: • Gorilla - Up on toes, arms raised, and growling • Bow & Arrow – Squat down as you act like you are shooting a bow & arrow and say, “ Boink!” • International sign for Mankind - Hands folded across chest, head tilted Determining the winner follows these progressions: • Man controls the Bow & Arrow so the man wins. • Bow & Arrow can “Boink” (shoot) the Gorilla so the Bow & Arrow wins over the Gorilla. • Gorilla can crush/hug the Man so the Gorilla wins over the Man. “Photo” hunt - This game is played with a partner. One person is the photographer and the other is the camera. The camera stands in front of the photographer with their eyes closed. The photographer will “trust walk” them around the area with their hands on the camera’s shoulder. The photographer will walk them around the area and take 3 pictures. To take a picture the camera will be hear “click” or some other camera cue noise. That is their cue to open their eyes for 2 seconds and then to shut them. After all three pictures are taken the camera will be walked around in a confusing manner back to the start. It is now the job of the camera to see if they can find the exact locations that they took their pictures. Silent interview -For this game, participants will be split into groups of 2 and given 3 questions. One person in the group will try and “answer” those 3 questions without any verbal communication. It is the job of the other participant to try and figure out what they are being told. Once the partners have switched roles and both have had their opportunity to answer the questions they can share to see if they were correct. For added fun if anyone has a really good demonstration feel free to allow them to showcase it for the whole group. Some examples of questions are favorite food, book, movie, etc… Yee Haw - Camouflage - This is a game that can be played anywhere and kids love it. Establish some kind of boundaries, for example you can not go more than 25 feet from where I am standing. The way the game is played is one person screams “camouflage” and then they begin counting with their eyes closed for a predetermined amount of time, lets say 15 seconds. Those that are not counting are running out and trying to camouflage or hide from the counter or “it”. Once the 15 seconds is over “it” will try and look around them to see if they can find anyone. “It” is not able to move their feet, they must stay in one place at all times. After “it” has found as many people as they can they will count again with their eyes closed, this time lets say for 5 seconds. During this recount those hiding will try and make their way closer to “it”. The game is won when a person can successfully avoid detection and tag “its” foot during the countdowns. You can recount as many times as you would like or until all players have been seen or won. Avalanche - This game can be used in transit from one location to another. As your group is making their way to an area someone will scream, “avalanche.” Once this happens campers have 5 seconds to get them selves out of the way of the avalanche. This is achieved by getting yourself off the ground for a full 3 seconds. This can be by balancing on a rock, hanging from a stable tree limb, or any other safe and creative way campers come up with. Cherokee sticks - This is one of those mental teasers. You can tell a story about how the Native Americans needed to communicate but they all spoke different languages. In order to trade the “Cherokee’s” developed a number system that all of the tribes understood. Tell them that you have learned this system and would like to see if they can figure it out. Start out by gathering a few small twigs or rocks. What you will do is assemble the sticks or rocks in some type of pattern in front of them. The real number is not shown by the objects in front of them, it is represented you the # of fingers that you are showing in the background. For example, I place 6 rocks in a circular pattern, when I ask them what number they see I have placed 3 fingers on the table or ground behind my pile of rocks. The answer to my question is 3 because that is how many fingers that I am showing, the rocks are just a distraction. It doesn’t matter how many objects are in front of them, it is fun to change it up each time. Let them see if they can figure out the secret. Polar bear game - This is a mental teaser. The phrase Between ______, and ______, and ______, how many polar bears do you see. The goal is for campers to figure out “how many polar bears there are”. The answer is in the questions. It is determined by the number of words said after your third boundary marker. So the answer to my example is 7. Another example is, between beber, Perlman and dc, how many polar bears are there. The answer is 6. Give the phrase a few times and then give answers, over time kids will start to see the pattern. Minute mysteries- There are many different riddles that can be solved by using yes or no questions. I will try and make a book of them. I have a book that we can give title too Johnny woops - This is a repeat after me game with a mental twist. You will demonstrate to campers a pattern and tell them that they must do everything that you do. Start out by holding your left hand out in front of you with your fingers spread apart. With your right hand and starting with your pinky you say the name Johnny. You repeat Johnny for each finger on your hand making your way towards your thumb. After your index finger and before you reach your thumb you say the word “woops” as you slide your right index finger down and back up towards the tip of your thumb. Once at your thumb you say Johnny and make your way back towards your pinky making sure to slide up towards the top of your index finger again saying the word woops. Your phrase will be, “Johnny, Johnny, Johnny, Johnny, whoops, Johnny, whoops, Johnny, Johnny, Johnny, Johnny.” Once you complete the phrase you cross your arms.
Load more

Recommended publications
  • CS599: Algorithm Design in Strategic Settings Fall 2012 Lecture 2: Game Theory Preliminaries
    CS599: Algorithm Design in Strategic Settings Fall 2012 Lecture 2: Game Theory Preliminaries Instructor: Shaddin Dughmi Administrivia Website: http://www-bcf.usc.edu/~shaddin/cs599fa12 Or go to www.cs.usc.edu/people/shaddin and follow link Emails? Registration Outline 1 Games of Complete Information 2 Games of Incomplete Information Prior-free Games Bayesian Games Outline 1 Games of Complete Information 2 Games of Incomplete Information Prior-free Games Bayesian Games Example: Rock, Paper, Scissors Figure: Rock, Paper, Scissors Games of Complete Information 2/23 Rock, Paper, Scissors is an example of the most basic type of game. Simultaneous move, complete information games Players act simultaneously Each player incurs a utility, determined only by the players’ (joint) actions. Equivalently, player actions determine “state of the world” or “outcome of the game”. The payoff structure of the game, i.e. the map from action vectors to utility vectors, is common knowledge Games of Complete Information 3/23 Typically thought of as an n-dimensional matrix, indexed by a 2 A, with entry (u1(a); : : : ; un(a)). Also useful for representing more general games, like sequential and incomplete information games, but is less natural there. Figure: Generic Normal Form Matrix Standard mathematical representation of such games: Normal Form A game in normal form is a tuple (N; A; u), where N is a finite set of players. Denote n = jNj and N = f1; : : : ; ng. A = A1 × :::An, where Ai is the set of actions of player i. Each ~a = (a1; : : : ; an) 2 A is called an action profile. u = (u1; : : : un), where ui : A ! R is the utility function of player i.
    [Show full text]
  • Chapter 16 Oligopoly and Game Theory Oligopoly Oligopoly
    Chapter 16 “Game theory is the study of how people Oligopoly behave in strategic situations. By ‘strategic’ we mean a situation in which each person, when deciding what actions to take, must and consider how others might respond to that action.” Game Theory Oligopoly Oligopoly • “Oligopoly is a market structure in which only a few • “Figuring out the environment” when there are sellers offer similar or identical products.” rival firms in your market, means guessing (or • As we saw last time, oligopoly differs from the two ‘ideal’ inferring) what the rivals are doing and then cases, perfect competition and monopoly. choosing a “best response” • In the ‘ideal’ cases, the firm just has to figure out the environment (prices for the perfectly competitive firm, • This means that firms in oligopoly markets are demand curve for the monopolist) and select output to playing a ‘game’ against each other. maximize profits • To understand how they might act, we need to • An oligopolist, on the other hand, also has to figure out the understand how players play games. environment before computing the best output. • This is the role of Game Theory. Some Concepts We Will Use Strategies • Strategies • Strategies are the choices that a player is allowed • Payoffs to make. • Sequential Games •Examples: • Simultaneous Games – In game trees (sequential games), the players choose paths or branches from roots or nodes. • Best Responses – In matrix games players choose rows or columns • Equilibrium – In market games, players choose prices, or quantities, • Dominated strategies or R and D levels. • Dominant Strategies. – In Blackjack, players choose whether to stay or draw.
    [Show full text]
  • Guiding Mathematical Discovery How We Started a Math Circle
    Guiding Mathematical Discovery How We Started a Math Circle Jackie Chan, Tenzin Kunsang, Elisa Loy, Fares Soufan, Taylor Yeracaris Advised by Professor Deanna Haunsperger Illustrations by Elisa Loy Carleton College, Mathematics and Statistics Department 2 Table of Contents About the Authors 4 Acknowledgments 6 Preface 7 Designing Circles 9 Leading Circles 11 Logistics & Classroom Management 14 The Circles 18 Shapes and Patterns 20 ​ Penny Shapes 21 Polydrons 23 Knots and What-Not 25 Fractals 28 Tilings and Tessellations 31 Graphs and Trees 35 ​ The Four Islands Problem (Königsberg Bridge Problem) 36 Human Graphs 39 Map Coloring 42 Trees: Dots and Lines 45 Boards and Spatial Reasoning 49 ​ Filing Grids 50 Gerrymandering Marcellusville 53 Pieces on a Chessboard 58 Games and Strategy 63 ​ Game Strategies (Rock/Paper/Scissors) 64 Game Strategies for Nim 67 Tic-Tac-Torus 70 SET 74 KenKen Puzzles 77 3 Logic and Probability 81 ​ The Monty Hall Problem 82 Knights and Knaves 85 Sorting Algorithms 87 Counting and Combinations 90 ​ The Handshake/High Five Problem 91 Anagrams 96 Ciphers 98 Counting Trains 99 But How Many Are There? 103 Numbers and Factors 105 ​ Piles of Triangular Numbers 106 Cup Flips 108 Counting with Cups — The Josephus Problem 111 Water Cups 114 Guess What? 116 Additional Circle Ideas 118 Further Reading 120 Keyword Index 121 4 About the Authors Jackie Chan Jackie is a senior computer science and mathematics major at Carleton College who has had an interest in teaching mathematics since an early age. Jackie’s interest in mathematics education stems from his enjoyment of revealing the intuition behind mathematical concepts.
    [Show full text]
  • Problem Set #8 Solutions: Introduction to Game Theory
    Finance 30210 Solutions to Problem Set #8: Introduction to Game Theory 1) Consider the following version of the prisoners dilemma game (Player one’s payoffs are in bold): Player Two Cooperate Cheat Player One Cooperate $10 $10 $0 $12 Cheat $12 $0 $5 $5 a) What is each player’s dominant strategy? Explain the Nash equilibrium of the game. Start with player one: If player two chooses cooperate, player one should choose cheat ($12 versus $10) If player two chooses cheat, player one should also cheat ($0 versus $5). Therefore, the optimal strategy is to always cheat (for both players) this means that (cheat, cheat) is the only Nash equilibrium. b) Suppose that this game were played three times in a row. Is it possible for the cooperative equilibrium to occur? Explain. If this game is played multiple times, then we start at the end (the third playing of the game). At the last stage, this is like a one shot game (there is no future). Therefore, on the last day, the dominant strategy is for both players to cheat. However, if both parties know that the other will cheat on day three, then there is no reason to cooperate on day 2. However, if both cheat on day two, then there is no incentive to cooperate on day one. 2) Consider the familiar “Rock, Paper, Scissors” game. Two players indicate either “Rock”, “Paper”, or “Scissors” simultaneously. The winner is determined by Rock crushes scissors Paper covers rock Scissors cut paper Indicate a -1 if you lose and +1 if you win.
    [Show full text]
  • Project in Mathematics Dan Saattrup Nielsen Advisor: Asger
    Games and determinacy Project in Mathematics Dan Saattrup Nielsen Advisor: Asger T¨ornquist Date: 17/04-2015 iii of 42 Abstract In this project we introduce the notions of perfect information games in a set- theoretic context, from where we’ll analyse both the consequences of the deter- minacy of games as well as showing large classes of games are determined. More precisely, we’ll show that determinacy of games over the reals implies that every subset of the reals is Lebesgue measurable and has both the Baire and perfect set property (thereby contradicting the axiom of choice). Next, Martin’s result on Borel determinacy will be presented, as well as his proof of analytic determinacy from the existence of a Ramsey cardinal. Lastly, we’ll present a certain kind of stochastic games (that is, games involving chance) called Blackwell games, and present Martin’s proof that determinacy of perfect information games imply the determinacy of Blackwell games. iv of 42 Dan Saattrup Nielsen Contents Introduction v 1 Basic game theory 1 1.1 Infinite games . .1 1.2 Regularity properties and games . .2 1.3 Axiom of determinacy . .9 2 Borel determinacy 11 2.1 Determinacy of open and closed games . 11 2.2 Borel determinacy . 12 3 Analytic determinacy 20 3.1 Ramsey cardinals . 20 3.2 Kleene-Brouwer ordering . 21 3.3 Analytic determinacy . 22 4 Blackwell determinacy 26 4.1 Blackwell games . 26 4.2 Blackwell determinacy . 28 A Preliminaries 38 A.1 Polish spaces and trees . 38 A.2 Borel and analytic sets . 39 A.3 Baire property .
    [Show full text]
  • Lecture 3 1 Introduction to Game Theory 2 Games of Complete
    CSCI699: Topics in Learning and Game Theory Lecture 3 Lecturer: Shaddin Dughmi Scribes: Brendan Avent, Cheng Cheng 1 Introduction to Game Theory Game theory is the mathematical study of interaction among rational decision makers. The goal of game theory is to predict how agents behave in a game. For instance, poker, chess, and rock-paper-scissors are all forms of widely studied games. To formally define the concepts in game theory, we use Bayesian Decision Theory. Explicitly: • Ω is the set of future states. For example, in rock-paper-scissors, the future states can be 0 for a tie, 1 for a win, and -1 for a loss. • A is the set of possible actions. For example, the hand form of rock, paper, scissors in the game of rock-paper-scissors. • For each a ∈ A, there is a distribution x(a) ∈ Ω for which an agent believes he will receive ω ∼ x(a) if he takes action a. • A rational agent will choose an action according to Expected Utility theory; that is, each agent has their own utility function u :Ω → R, and chooses an action a∗ ∈ A that maximizes the expected utility . ∗ – Formally, a ∈ arg max E [u(ω)]. a∈A ω∼x(a) – If there are multiple actions that yield the same maximized expected utility, the agent may randomly choose among them. 2 Games of Complete Information 2.1 Normal Form Games In games of complete information, players act simultaneously and each player’s utility is determined by his actions as well as other players’ actions. The payoff structure of 1 2 GAMES OF COMPLETE INFORMATION 2 the game (i.e., the map from action profiles to utility vectors) is common knowledge to all players in the game.
    [Show full text]
  • Evolution of Restraint in a Structured Rock–Paper–Scissors Community
    Evolution of restraint in a structured rock–paper–scissors community Joshua R. Nahum, Brittany N. Harding, and Benjamin Kerr1 Department of Biology and BEACON Center for the Study of Evolution in Action, University of Washington, Seattle, WA 98195 Edited by John C. Avise, University of California, Irvine, CA, and approved April 19, 2011 (received for review January 31, 2011) It is not immediately clear how costly behavior that benefits others ately experience beneficial social environments (engineered by evolves by natural selection. By saving on inherent costs, individ- their kin), whereas selfish individuals tend to face a milieu lack- uals that do not contribute socially have a selective advantage ing prosocial behavior (because their kin tend to be less altru- over altruists if both types receive equal benefits. Restrained istic). Interaction with kin can occur actively through the choice consumption of a common resource is a form of altruism. The cost of relatives as social contacts or passively through the interaction of this kind of prudent behavior is that restrained individuals give with neighbors in a habitat with limited dispersal. There is now up resources to less-restrained individuals. The benefit of restraint a large body of literature on the effect of active and passive as- is that better resource management may prolong the persistence sortment on the evolution of altruism (5, 11–18). At a funda- of the group. One way to dodge the problem of defection is for mental level, this research focuses on the distribution of inter- altruists to interact disproportionately with other altruists. With actions among altruistic and selfish individuals.
    [Show full text]
  • Lecture 8 — May 5 Lecturer: Juli´Anmestre
    Optimization Summer 2010 Lecture 8 | May 5 Lecturer: Juli´anMestre 8.1 Two-player zero-sum games We consider the following mathematical abstraction of a game played by two players. Each player has a set of possible strategies that she can choose to play. We denote by Si the set of strategies of player i = 1; 2. The outcome of the game is determined by jS1|×|S2j the pay-off matrix D 2 R . Suppose that the players select s1 2 S1 and s2 2 S2 respectively. Then if D(s1; s2) > 0 we can think of player 1 getting D(s1; s2) euros from player 2, and if D(s1; s2) < 0 we can think of player 1 paying jD(s1; s2)j euros to player 2. This type of games are call zero-sum because the sum of the earnings of player 1 and player 2 is always zero. For a concrete example, consider the children game of rock-paper-scissors. The strat- egy of the each player is the same, frock, paper, scissorg, and the pay-off matrix is as follows: rock paper scissors rock 0 -1 1 paper 1 0 -1 scissors -1 1 0 Clearly if a player has to announce her strategy before the other payer, there is no way she can win. An interesting question to consider is whether she could do better by using a randomized strategy? Let us try to make this question more precise. Suppose we are given a pay-off matrix D 2 Rn×m. A mixed strategy for player 1 is a vector x 2 Rn P such that xi ≥ 0 for all i and i xi = 1, where xi represents the probability that payer 1 choose her ith strategy.
    [Show full text]
  • Cycles, Diversity and Competition in Rock-Paper-Scissors-Lizard-Spock Spatial Game Agent Simulations
    Cycles, Diversity and Competition in Rock-Paper-Scissors-Lizard-Spock Spatial Game Agent Simulations K.A. Hawick Computer Science, Institute for Information and Mathematical Sciences, Massey University, North Shore 102-904, Auckland, New Zealand email: [email protected] Tel: +64 9 414 0800 Fax: +64 9 441 8181 ABSTRACT The emergence of complex spatial patterns in agent-based models is closely connected with the symmetries and re- lationships present between individual microscopic con- stituents. Games such as Rock-Paper-Scissors (RPS) have a closed cycle relationship amongst players which extends the symmetry. RPS and related games can be played by agents arranged on a spatial grid and have been shown to generate many complex spatial patterns. We consider the implications of extending the individual RPS game com- plexity to five-cycle games such as “Rock-Paper-Scissors- Lizard-Spock” that have competing cyclic reactions. We simulate large spatial systems using a reaction-rate formu- lation which are simulated for long run times to capture the dynamic equilibrium regime. We report on the stable and unstable phase mixtures that arise in these agent models Figure 1: Snapshot configuration of the Rock, Paper, Scis- and comment on the effects that drive them. sors, Lizard, Spock! game on a 1024 × 768 spatial mesh, 2048 steps after a random start. KEY WORDS rock paper scissors lizard Spock; game theory; agents; spa- terns that emerge in simulated systems. Figure 1 shows a tial complexity; emergence. typical spatial pattern arising in these models. A system of spatial agents is initialised randomly and is subsequently evolved in simulation time according to microscopically 1 Introduction simple probabilistic rules.
    [Show full text]
  • The Minimax Theorem and Algorithms for Linear Programming∗
    CS261: A Second Course in Algorithms Lecture #10: The Minimax Theorem and Algorithms for Linear Programming∗ Tim Roughgardeny February 4, 2016 1 Zero-Sum Games and the Minimax Theorem 1.1 Rock-Paper Scissors Recall rock-paper-scissors (or roshambo). Two players simultaneously choose one of rock, paper, or scissors, with rock beating scissors, scissors beating paper, and paper beating rock.1 Here's an idea: what if I made you go first? That's obviously unfair | whatever you do, I can respond with the winning move. But what if I only forced you to commit to a probability distribution over rock, paper, and scissors? (Then I respond, then nature flips coins on your behalf.) If you prefer, imagine that you submit your code for a (randomized) algorithm for choosing an action, then I have to choose my action, and then we run your algorithm and see what happens. In the second case, going first no longer seems to doom you. You can protect yourself by randomizing uniformly among the three options | then, no matter what I do, I'm equally likely to win, lose, or tie. The minimax theorem states that, in general games of \pure competition," a player moving first can always protect herself by randomizing appropriately. ∗ c 2016, Tim Roughgarden. yDepartment of Computer Science, Stanford University, 474 Gates Building, 353 Serra Mall, Stanford, CA 94305. Email: [email protected]. 1Here are some fun facts about rock-paper-scissors. There's a World Series of RPS every year, with a top prize of at least $50K. If you watch some videos of them, you will see pure psychological welfare.
    [Show full text]
  • Pure Saddle Points and Symmetric Relative Payoff Games∗
    University of Heidelberg Department of Economics Discussion Paper Series No. 500 Pure Saddle Points and Symmetric Relative Payoff Games Peter Duersch, Jörg Oechssler, Burkhard C. Schipper March 2010 Pure Saddle Points and Symmetric Relative Payoff Games∗ Peter Duerschy J¨orgOechsslerz Burkhard C. Schipperx February 21, 2010 Abstract It is well known that the rock-paper-scissors game has no pure saddle point. We show that this holds more generally: A symmetric two-player zero-sum game has a pure saddle point if and only if it is not a generalized rock-paper-scissors game. Moreover, we show that every finite symmetric quasiconcave two-player zero-sum game has a pure saddle point. Further sufficient conditions for existence are pro- vided. We apply our theory to a rich collection of examples by noting that the class of symmetric two-player zero-sum games coincides with the class of relative payoff games associated with symmetric two-player games. This allows us to derive results on the existence of a finite population evolutionary stable strategies. Keywords: Symmetric two-player games, zero-sum games, Rock-Paper-Scissors, single-peakedness, quasiconcavity, finite population evolutionary stable strategy, increasing differences, decreasing differences, potentials, additive separability. JEL-Classifications: C72, C73. ∗Some of the material has previously been part of the paper \Unbeatable imitation" presented at the International Conference on Game Theory in Stony Brook, 2009. yDepartment of Economics, University of Heidelberg zDepartment of Economics, University of Heidelberg, Email: [email protected] xDepartment of Economics, University of California, Davis, Email: [email protected] 1 Introduction Many zero-sum games do not have a solution without allowing for mixed actions.
    [Show full text]
  • MIT 14.16 S16 Strategy and Information Lecture Slides
    Strategy & Information Mihai Manea MIT What is Game Theory? Game Theory is the formal study of strategic interaction. In a strategic setting the actions of several agents are interdependent. Each agent’s outcome depends not only on his actions, but also on the actions of other agents. How to predict opponents’ play and respond optimally? Everything is a game. I poker, chess, soccer, driving, dating, stock market I advertising, setting prices, entering new markets, building a reputation I bargaining, partnerships, job market search and screening I designing contracts, auctions, insurance, environmental regulations I international relations, trade agreements, electoral campaigns Most modern economic research includes game theoretical elements. Eleven game theorists have won the economics Nobel Prize so far. Mihai Manea (MIT) Strategy & Information February 10, 2016 2 / 57 Brief History I Cournot (1838): quantity setting duopoly I Zermelo (1913): backward induction I von Neumann (1928), Borel (1938), von Neumann and Morgenstern (1944): zero-sum games I Flood and Dresher (1950): experiments I Nash (1950): equilibrium I Selten (1965): dynamic games I Harsanyi (1967): incomplete information I Akerlof (1970), Spence (1973): first applications I 1980s boom, continuing nowadays: repeated games, bargaining, reputation, equilibrium refinements, industrial organization, contract theory, mechanism/market design I 1990s: parallel development of behavioral economics I more recently: applications to computer science, political science, psychology, evolutionary
    [Show full text]