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The first known discussion of game theory occurred in a letter written by James Waldegrave in 1713. In this letter, Waldegrave provides a minimax mixed strategy solution to a two-person version of the card game le Her. It was not until the publication of Antoine Augustin Cournot’s Researches into the Mathematical Principles of the Theory of Wealth in 1838 that a general game theoretic analysis was pursued. In this work Cournot considers a duopoly and presents a solution that is a restricted version of the Nash equilibrium.
Although Cournot’s analysis is more general than Waldegrave’s, game theory did not really exist as a unique field until John von Neumann published a series of papers in 1928. These results were later expanded in the 1944 book The Theory of Games and Economic Behavior by von Neumann and Oskar Morgenstern. This profound work contains the method for finding optimal solutions for two-person zero-sum games. During this time period, work on game theory was primarily focused on cooperative game theory, which analyzes optimal strategies for groups of individuals, presuming that they can enforce agreements between them about proper strategies.
In 1950, the first discussion of the Prisoner’s dilemma appeared, and an experiment was undertaken on this game at the RAND corporation. Around this same time, John Nash developed a definition of an “optimum” strategy for multiplayer games where no such optimum was previously defined, known as Nash equilibrium. This equilibrium is sufficiently general, allowing for the analysis of non-cooperative games in addition to cooperative ones.
Game theory experienced a flurry of activity in the 1950s, during which time the concepts of the core, the extensive form game, fictitious play, repeated games, and the Shapley value were developed. In addition, the first applications of Game theory to philosophy and political science occurred during this time.
In 1965, Reinhard Selten introduced his solution concept of subgame perfect equilibria, which further refined the Nash equilibrium (later he would introduce trembling hand perfection as well). In 1967, John Harsanyi developed the concepts of complete information and Bayesian games. He, along with John Nash and Reinhard Selten, won The Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel (also known as The Nobel Prize in Economics) in 1994.
In the 1970s, game theory was extensively applied in biology, largely as a result of the work of John Maynard Smith and his evolutionary stable strategy. In addition, the concepts of correlated equilibrium, trembling hand perfection, and common knowledge[5] were introduced and analyzed.
In 2005, game theorists Thomas Schelling and Robert Aumann won the Nobel Prize in Economics. Schelling worked on dynamic models, early examples of evolutionary game theory. Aumann contributed more to the equilibrium school, developing an equilibrium coarsening correlated equilibrium and developing extensive analysis of the assumption of common knowledge.
This guide is licensed under the GNU Free Documentation License. It uses material from the Wikipedia.
Symmetric and asymmetric
An asymmetric game
|
E |
F |
| E |
1, 2 |
0, 0 |
| F |
0, 0 |
1, 2 |
A symmetric game is a game where the payoffs for playing a particular strategy depend only on the other strategies employed, not on who is playing them. If the identities of the players can be changed without changing the payoff to the strategies, then a game is symmetric. Many of the commonly studied 2×2 games are symmetric. The standard representations of Chicken, the Prisoner’s Dilemma, and the Stag hunt are all symmetric games. [1]
Most commonly studied asymmetric games are games where there are not identical strategy sets for both players. For instance, the Ultimatum game and similar the Dictator game have different strategies for each player. It is possible, however, for a game to have identical strategies for both players, yet be asymmetric. For example, the game pictured to the right is asymmetric despite having identical strategy sets for both players.
Zero sum and non-zero sum
A Zero-Sum Game
|
A |
B |
| A |
2, -2 |
-1, 1 |
| B |
-1, 1 |
3, -3 |
In zero-sum games the total benefit to all players in the game, for every combination of strategies, always adds to zero (or more informally put, a player benefits only at the expense of others). Poker exemplifies a zero-sum game, because one wins exactly the amount one’s opponents lose. Other zero sum games include Matching pennies and most classical board games including Go and Chess. Many games studied by game theorists (including the famous Prisoner’s Dilemma) are non-zero-sum games, because some outcomes have net results greater or less than zero. Informally, in non-zero-sum games, a gain by one player does not necessarily correspond with a loss by another.
It is possible to transform any game into a zero-sum game by adding an additional dummy player (often called “the board”), whose losses compensate the players’ net winnings.
Simultaneous and sequential
Simultaneous games are games where both players move simultaneously, or if they do not move simultaneously, the later players are unaware of the earlier players’ actions (making them effectively simultaneous). Sequential games (or dynamic games) are games where later players have some knowledge about earlier actions. This need not be perfect knowledge about every action of earlier players; it might be very little information. For instance, a player may know that an earlier player did not perform one particular action, while she does not know which of the other available actions the first player actually performed.
The difference between simultaneous and sequential games is captured in the different representations discussed above. Normal form is used to represent simultaneous games, and extensive form is used to represent sequential ones.
Perfect information and imperfect information
A game of imperfect information (the dotted line represents ignorance on the part of player 2)
An important subset of sequential games consists of games of perfect information. A game is one of perfect information if all players know the moves previously made by all other players. Thus, only sequential games can be games of perfect information, since in simultaneous games not every player knows the actions of the others. Most games studied in game theory are imperfect information games, although some interesting games are games of perfect information, including the Ultimatum Game and Centipede Game. Many popular games are games of perfect information including Chess, Go, and Mancala.
Perfect information is often confused with complete information, which is a similar concept. Complete information requires that every player know the strategies and payoffs of the other players but not necessarily the actions.
Infinitely long games
For obvious reasons, games as studied by economists and real-world game players are generally finished in a finite number of moves. Pure mathematicians are not so constrained, and set theorists in particular study games that last for infinitely many moves, with the winner (or other payoff) not known until after all those moves are completed.
The focus of attention is usually not so much on what is the best way to play such a game, but simply on whether one or the other player has a winning strategy. (It can be proved, using the axiom of choice, that there are games—even with perfect information, and where the only outcomes are “win” or “lose”—for which neither player has a winning strategy.) The existence of such strategies, for cleverly designed games, has important consequences in descriptive set theory.
Notes
- ^ Some scholars would consider certain asymmetric games as examples of these games as well. However, the most common payoffs for each of these games are symmetric.
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The games studied by game theory are well-defined mathematical objects. A game consists of a set of players, a set of moves (or strategies) available to those players, and a specification of payoffs for each combination of strategies. There are two ways of representing games that are common in the literature.
Normal form
A normal form game
|
Player 2 chooses left |
Player 2 chooses right |
| Player 1 chooses top |
4, 3 |
-1, -1 |
| Player 1 chooses bottom |
0, 0 |
3, 4 |
The normal (or strategic form) game is a matrix which shows the players, strategies, and payoffs (see the example to the right). Here there are two players; one chooses the row and the other chooses the column. Each player has two strategies, which are specified by the number of rows and the number of columns. The payoffs are provided in the interior. The first number is the payoff received by the row player (Player 1 in our example); the second is the payoff for the column player (Player 2 in our example). Suppose that Player 1 plays top and that Player 2 plays left. Then Player 1 gets 4, and Player 2 gets 3.
When a game is presented in normal form, it is presumed that each player acts simultaneously or, at least, without knowing the actions of the other. If players have some information about the choices of other players, the game is usually presented in extensive form.
Extensive form
Extensive form games attempt to capture games with some important order. Games here are presented as trees (as pictured to the left). Here each vertex (or node) represents a point of choice for a player. The player is specified by a number listed by the vertex. The lines out of the vertex represent a possible action for that player. The payoffs are specified at the bottom of the tree.
In the game pictured here, there are two players. Player 1 moves first and chooses either F or U. Player 2 sees Player 1′s move and then chooses A or R. Suppose that Player 1 chooses U and then Player 2 chooses A, then Player 1 gets 8 and Player 2 gets 2.
Extensive form games can also capture simultaneous-move games as well. Either a dotted line or circle is drawn around two different vertices to represent them as being part of the same information set (i.e., the players do not know at which point they are).
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Game theory is a branch of applied mathematics that studies strategic situations where players choose different actions in an attempt to maximize their returns. First developed as a tool for understanding economic behavior, game theory is now used in many diverse academic fields, ranging from biology to philosophy. Game theory saw substantial growth during the Cold War because of its application to military strategy, most notably to the concept of mutually assured destruction. Beginning in the 1970s, game theory has been applied to animal behavior, including species’ development by natural selection. Because of interesting games like the Prisoner’s dilemma, where mutual self-interest hurts everyone, game theory has been used in ethics and philosophy. Finally, game theory has recently drawn attention from computer scientists because of its use in artificial intelligence and cybernetics.
In addition to its academic interest, game theory has received attention in popular culture. An important figure in game theory, John Nash was the subject of the 2001 film A Beautiful Mind. Several game shows have adopted game theoretic situations, including Friend or Foe and Deal or No Deal. [1]
Although similar to decision theory, game theory studies decisions that are made in an environment where various players interact. In other words, game theory studies choice of optimal behavior when costs and benefits of each option are not fixed, but depend upon the choices of other individuals.
Notes
- ^ GameTheory.net has an extensive list of references to game theory in popular culture.
References
- Textbooks and general reference texts
- Gibbons, Robert (1992) Game Theory for Applied Economists, Princeton University Press ISBN 0691003955 (readable; suitable for advanced undergraduates. Published in Europe by Harvester Wheatsheaf (London) with the title A primer in game theory)
- Ginits, Herbert (2000) Game Theory Evolving Princeton University Press ISBN 0691009430
- Osborne, Martin and Ariel Rubinstein: A Course in Game Theory, MIT Press, 1994, ISBN 0-262-65040-1 (modern introduction at the introductory graduate level)
- Fudenberg, Drew and Jean Tirole: Game Theory, MIT Press, 1991, ISBN 0262061414 (the definitive reference text)
- Historically important texts
- Fisher, Ronald (1930) The Genetical Theory of Natural Selection Clarendon Press, Oxford.
- Luce, Duncan and Howard Raiffa Games and Decisions: Introduction and Critical Survey Dover ISBN 0486659437
- Maynard Smith, John Evolution and the Theory of Games, Cambridge University Press 1982
- Morgenstern, Oskar and John von Neumann (1947) The Theory of Games and Economic Behavior Princeton University Press
- Nash, John (1950) “Equilibrium points in n-person games” Proceedings of the National Academy of the USA 36(1):48-49.
- Poundstone, William Prisoner’s Dilemma: John von Neumann, Game Theory and the Puzzle of the Bomb, ISBN 038541580X
- Other print references
- Camerer, Colin (2003) Behavioral Game Theory Princeton University Press ISBN 0691090394
- Gauthier, David (1987) Morals by Agreement Oxford University Press ISBN 0198249926
- Grim, Patrick, Trina Kokalis, Ali Alai-Tafti, Nicholas Kilb, and Paul St Denis (2004) “Making meaning happen.” Journal of Experimental & Theoretical Artificial Intelligence 16(4): 209-243.
- Kavka, Gregory (1986) Hobbesian Moral and Political Theory Princeton University Press. ISBN 069102765X
- Lewis, David (1969) Convention: A Philosophical Study
- Maynard Smith, J. and Harper, D. (2003) Animal Signals. Oxford University Press. ISBN 0198526857
- Quine, W.v.O (1967) “Truth by Convention” in Philosophica Essays for A.N. Whitehead Russel and Russel Publishers. ISBN 0846209705
- Quine, W.v.O (1960) “Carnap and Logical Truth” Synthese 12(4):350-374.
- Skyrms, Brian (1996) Evolution of the Social Contract Cambridge University Press. ISBN 0521555833
- Skyrms, Brian (2004) The Stag Hunt and the Evolution of Social Structure Cambridge University Press. ISBN 0521533929.
- Sober, Elliot and David Sloan Wilson (1999) Unto Others: The Evolution and Psychology of Unselfish Behavior Harvard University Press. ISBN 0674930479
- Websites
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