This article is about the mathematical study of strategic behavior. For the study of playing games for entertainment, seeGame studies."Game theorist" redirects here. For the YouTube series, seeGame Theorists.For other uses, seeGame theory (disambiguation).
Game theory is the study ofmathematical models of strategic interactions.[1] It has applications in many fields ofsocial science, and is used extensively ineconomics,logic,systems science andcomputer science.[2] Initially, game theory addressed two-personzero-sum games, in which a participant's gains or losses are exactly balanced by the losses and gains of the other participant. In the 1950s, it was extended to the study of non zero-sum games, and was eventually applied to a wide range ofbehavioral relations. It is now anumbrella term for thescience of rationaldecision making in humans, animals, and computers.
Game theory was developed extensively in the 1950s, and was explicitly applied toevolution in the 1970s, although similar developments go back at least as far as the 1930s. Game theory has been widely recognized as an important tool in many fields.John Maynard Smith was awarded theCrafoord Prize for his application ofevolutionary game theory in 1999, and fifteen game theorists have won theNobel Prize in economics as of 2020, including most recentlyPaul Milgrom andRobert B. Wilson.
Discussions on the mathematics of games began long before the rise of modern, mathematical game theory.Cardano wrote on games of chance inLiber de ludo aleae (Book on Games of Chance), written around 1564 but published posthumously in 1663.[4] Influenced by the work ofFermat andPascal on theproblem of points,Huygens developed the concept ofexpectation on reasoning about the structure of games of chance, publishing his gambling calculus inDe ratiociniis in ludo aleæ (On Reasoning in Games of Chance) in 1657.[5]
In 1713, a letter attributed to Charles Waldegrave, an activeJacobite and uncle to British diplomatJames Waldegrave, analyzed a game called "le her". Waldegrave provided aminimaxmixed strategy solution to a two-person version of the card game, and the problem is now known as theWaldegrave problem.[6][7]
In 1838,Antoine Augustin Cournot provided amodel of competition inoligopolies. Though he did not refer to it as such, he presented a solution that is theNash equilibrium of the game in hisRecherches sur les principes mathématiques de la théorie des richesses (Researches into the Mathematical Principles of the Theory of Wealth). In 1883,Joseph Bertrand critiqued Cournot's model as unrealistic, providing an alternative model of price competition[8] which would later be formalized byFrancis Ysidro Edgeworth.[9]
In 1913,Ernst Zermelo publishedÜber eine Anwendung der Mengenlehre auf die Theorie des Schachspiels (On an Application of Set Theory to the Theory of the Game of Chess), which proved that the optimal chess strategy isstrictly determined.[10]
The work ofJohn von Neumann established game theory as its own independent field in the early-to-mid 20th century, with von Neumann publishing his paperOn the Theory of Games of Strategy in 1928.[11][12] Von Neumann's original proof usedBrouwer's fixed-point theorem on continuousmappings into compactconvex sets, which became a standard method in game theory andmathematical economics. Von Neumann's work in game theory culminated in his 1944 bookTheory of Games and Economic Behavior, co-authored withOskar Morgenstern.[13] The second edition of this book provided anaxiomatic theory of utility, which reincarnatedDaniel Bernoulli's old theory of utility (of money) as an independent discipline. This foundational work contains the method for finding mutually consistent solutions for two-person zero-sum games. Subsequent work focused primarily oncooperative game theory, which analyzes optimal strategies for groups of individuals, presuming that they can enforce agreements between them about proper strategies.[14]
In his 1938 bookApplications aux Jeux de Hasard and earlier notes,Émile Borel proved aminimax theorem for two-person zero-sum matrix games only when the pay-off matrix is symmetric and provided a solution to a non-trivial infinite game (known in English asBlotto game). Borel conjectured the non-existence of mixed-strategy equilibria infinite two-person zero-sum games, a conjecture that was proved false by von Neumann.[15]
In 1950,John Nash developed a criterion for mutual consistency of players' strategies known as theNash equilibrium, applicable to a wider variety of games than the criterion proposed by von Neumann and Morgenstern. Nash proved that every finite n-player, non-zero-sum (not just two-player zero-sum)non-cooperative game has what is now known as a Nash equilibrium in mixed strategies.
In 1994, John Nash was awarded the Nobel Memorial Prize in the Economic Sciences for his contribution to game theory. Nash's most famous contribution to game theory is the concept of the Nash equilibrium, which is a solution concept fornon-cooperative games, published in 1951. A Nash equilibrium is a set of strategies, one for each player, such that no player can improve their payoff by unilaterally changing their strategy.
In 2005, game theoristsThomas Schelling andRobert Aumann followed Nash, Selten, and Harsanyi as Nobel Laureates. Schelling worked on dynamic models, early examples ofevolutionary game theory. Aumann contributed more to the equilibrium school, introducing equilibrium coarsening and correlated equilibria, and developing an extensive formal analysis of the assumption of common knowledge and of its consequences.
In 2012,Alvin E. Roth andLloyd S. Shapley were awarded the Nobel Prize in Economics "for the theory of stable allocations and the practice of market design". In 2014, the Nobel went to game theoristJean Tirole.
A game iscooperative if the players are able to form binding commitments externally enforced (e.g. throughcontract law). A game isnon-cooperative if players cannot form alliances or if all agreements need to beself-enforcing (e.g. throughcredible threats).[17]
Cooperative games are often analyzed through the framework ofcooperative game theory, which focuses on predicting which coalitions will form, the joint actions that groups take, and the resulting collective payoffs. It is different fromnon-cooperative game theory which focuses on predicting individual players' actions and payoffs by analyzingNash equilibria.[18][19]
Cooperative game theory provides a high-level approach as it describes only the structure and payoffs of coalitions, whereas non-cooperative game theory also looks at how strategic interaction will affect the distribution of payoffs. As non-cooperative game theory is more general, cooperative games can be analyzed through the approach of non-cooperative game theory (the converse does not hold) provided that sufficient assumptions are made to encompass all the possible strategies available to players due to the possibility of external enforcement of cooperation.
A symmetric game is a game where each player earns the same payoff when making the same choice. In other words, the identity of the player does not change the resulting game facing the other player.[20] Many of the commonly studied 2×2 games are symmetric. The standard representations ofchicken,the prisoner's dilemma, and thestag hunt are all symmetric games.
The most commonly studied asymmetric games are games where there are not identical strategy sets for both players. For instance, theultimatum game and similarly thedictator 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 in this section's graphic is asymmetric despite having identical strategy sets for both players.
Zero-sum games (more generally, constant-sum games) are games in which choices by players can neither increase nor decrease the available resources. In zero-sum games, the total benefit goes to all players in a game, for every combination of strategies, and always adds to zero (more informally, a player benefits only at the equal expense of others).[21]Poker exemplifies a zero-sum game (ignoring the possibility of the house's cut), because one wins exactly the amount one's opponents lose. Other zero-sum games includematching pennies and most classical board games includingGo andchess.
Many games studied by game theorists (including the famed prisoner's dilemma) are non-zero-sum games, because theoutcome has 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.
Furthermore,constant-sum games correspond to activities like theft and gambling, but not to the fundamental economic situation in which there are potentialgains from trade. It is possible to transform any constant-sum game into a (possibly asymmetric) zero-sum game by adding a dummy player (often called "the board") whose losses compensate the players' net winnings.
Simultaneous games are games where both players move simultaneously, or instead the later players are unaware of the earlier players' actions (making themeffectively simultaneous).Sequential games (a type of dynamic games) are games where players do not make decisions simultaneously, and player's earlier actions affect the outcome and decisions of other players.[22] This need not beperfect information about every action of earlier players; it might be very little knowledge. For instance, a player may know that an earlier player did not perform one particular action, while they do 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. Often,normal form is used to represent simultaneous games, whileextensive form is used to represent sequential ones. The transformation of extensive to normal form is one way, meaning that multiple extensive form games correspond to the same normal form. Consequently, notions of equilibrium for simultaneous games are insufficient for reasoning about sequential games; seesubgame perfection.
In short, the differences between sequential and simultaneous games are as follows:
A game of imperfect information. The dotted line represents ignorance on the part of player 2, formally called aninformation set.
An important subset of sequential games consists of games of perfect information. A game with perfect information means that all players, at every move in the game, know the previous history of the game and the moves previously made by all other players. An imperfect information game is played when the players do not know all moves already made by the opponent such as a simultaneous move game.[23] Examples of perfect-information games includetic-tac-toe,checkers,chess, andGo.[24][25][26]
Many card games are games of imperfect information, such aspoker andbridge.[27] Perfect information is often confused withcomplete information, which is a similar concept pertaining to the common knowledge of each player's sequence, strategies, and payoffs throughout gameplay.[28] Complete information requires that every player know the strategies and payoffs available to the other players but not necessarily the actions taken, whereas perfect information is knowledge of all aspects of the game and players.[29] Games ofincomplete information can be reduced, however, to games of imperfect information by introducing "moves by nature".[30]
One of the assumptions of the Nash equilibrium is that every player has correct beliefs about the actions of the other players. However, there are many situations in game theory where participants do not fully understand the characteristics of their opponents. Negotiators may be unaware of their opponent's valuation of the object of negotiation, companies may be unaware of their opponent's cost functions, combatants may be unaware of their opponent's strengths, and jurors may be unaware of their colleague's interpretation of the evidence at trial. In some cases, participants may know the character of their opponent well, but may not know how well their opponent knows his or her own character.[31]
Bayesian game means a strategic game with incomplete information. For a strategic game, decision makers are players, and every player has a group of actions. A core part of the imperfect information specification is the set of states. Every state completely describes a collection of characteristics relevant to the player such as their preferences and details about them. There must be a state for every set of features that some player believes may exist.[32]
Example of a Bayesian game
For example, where Player 1 is unsure whether Player 2 would rather date her or get away from her, while Player 2 understands Player 1's preferences as before. To be specific, supposing that Player 1 believes that Player 2 wants to date her under a probability of 1/2 and get away from her under a probability of 1/2 (this evaluation comes from Player 1's experience probably: she faces players who want to date her half of the time in such a case and players who want to avoid her half of the time). Due to the probability involved, the analysis of this situation requires to understand the player's preference for the draw, even though people are only interested in pure strategic equilibrium.
Games in which the difficulty of finding an optimal strategy stems from the multiplicity of possible moves are called combinatorial games. Examples include chess andGo. Games that involveimperfect information may also have a strong combinatorial character, for instancebackgammon. There is no unified theory addressing combinatorial elements in games. There are, however, mathematical tools that can solve some particular problems and answer some general questions.[33]
Games of perfect information have been studied incombinatorial game theory, which has developed novel representations, e.g.surreal numbers, as well ascombinatorial andalgebraic (andsometimes non-constructive) proof methods tosolve games of certain types, including "loopy" games that may result in infinitely long sequences of moves. These methods address games with higher combinatorial complexity than those usually considered in traditional (or "economic") game theory.[34][35] A typical game that has been solved this way isHex. A related field of study, drawing fromcomputational complexity theory, isgame complexity, which is concerned with estimating the computational difficulty of finding optimal strategies.[36]
Research inartificial intelligence has addressed both perfect and imperfect information games that have very complex combinatorial structures (like chess, go, or backgammon) for which no provable optimal strategies have been found. The practical solutions involve computational heuristics, likealpha–beta pruning or use ofartificial neural networks trained byreinforcement learning, which make games more tractable in computing practice.[33][37]
Much of game theory is concerned with finite, discrete games that have a finite number of players, moves, events, outcomes, etc. Many concepts can be extended, however.Continuous games allow players to choose a strategy from a continuous strategy set. For instance,Cournot competition is typically modeled with players' strategies being any non-negative quantities, including fractional quantities.
Differential games such as the continuouspursuit and evasion game are continuous games where the evolution of the players' state variables is governed bydifferential equations. The problem of finding an optimal strategy in a differential game is closely related to theoptimal control theory. In particular, there are two types of strategies: the open-loop strategies are found using thePontryagin maximum principle while the closed-loop strategies are found usingBellman's Dynamic Programming method.
A particular case of differential games are the games with a randomtime horizon.[38] In such games, the terminal time is a random variable with a givenprobability distribution function. Therefore, the players maximize themathematical expectation of the cost function. It was shown that the modified optimization problem can be reformulated as a discounted differential game over an infinite time interval.
Evolutionary game theory studies players who adjust their strategies over time according to rules that are not necessarily rational or farsighted.[39] In general, the evolution of strategies over time according to such rules is modeled as aMarkov chain with a state variable such as the current strategy profile or how the game has been played in the recent past. Such rules may feature imitation, optimization, or survival of the fittest.
In biology, such models can representevolution, in which offspring adopt their parents' strategies and parents who play more successful strategies (i.e. corresponding to higher payoffs) have a greater number of offspring. In the social sciences, such models typically represent strategic adjustment by players who play a game many times within their lifetime and, consciously or unconsciously, occasionally adjust their strategies.[40]
Stochastic outcomes (and relation to other fields)
Individual decision problems with stochastic outcomes are sometimes considered "one-player games". They may be modeled using similar tools within the related disciplines ofdecision theory,operations research, and areas ofartificial intelligence, particularlyAI planning (with uncertainty) andmulti-agent system. Although these fields may have different motivators, the mathematics involved are substantially the same, e.g. usingMarkov decision processes (MDP).[41]
Stochastic outcomes can also be modeled in terms of game theory by adding a randomly acting player who makes "chance moves" ("moves by nature").[42] This player is not typically considered a third player in what is otherwise a two-player game, but merely serves to provide a roll of the dice where required by the game.
For some problems, different approaches to modeling stochastic outcomes may lead to different solutions. For example, the difference in approach between MDPs and theminimax solution is that the latter considers the worst-case over a set of adversarial moves, rather than reasoning in expectation about these moves given a fixed probability distribution. The minimax approach may be advantageous where stochastic models of uncertainty are not available, but may also be overestimating extremely unlikely (but costly) events, dramatically swaying the strategy in such scenarios if it is assumed that an adversary can force such an event to happen.[43] (SeeBlack swan theory for more discussion on this kind of modeling issue, particularly as it relates to predicting and limiting losses in investment banking.)
General models that include all elements of stochastic outcomes, adversaries, and partial or noisy observability (of moves by other players) have also been studied. The "gold standard" is considered to be partially observablestochastic game (POSG), but few realistic problems are computationally feasible in POSG representation.[43]
These are games the play of which is the development of the rules for another game, the target or subject game.Metagames seek to maximize the utility value of the rule set developed. The theory of metagames is related tomechanism design theory.
The termmetagame analysis is also used to refer to a practical approach developed by Nigel Howard,[44] whereby a situation is framed as a strategic game in which stakeholders try to realize their objectives by means of the options available to them. Subsequent developments have led to the formulation ofconfrontation analysis.
Mean field game theory is the study of strategic decision making in very large populations of small interacting agents. This class of problems was considered in the economics literature byBoyan Jovanovic andRobert W. Rosenthal, in the engineering literature byPeter E. Caines, and by mathematiciansPierre-Louis Lions and Jean-Michel Lasry.
The games studied in game theory are well-defined mathematical objects. To be fully defined, a game must specify the following elements: theplayers of the game, theinformation andactions available to each player at each decision point, and thepayoffs for each outcome. (Eric Rasmusen refers to these four "essential elements" by the acronym "PAPI".)[45][46][47][48] A game theorist typically uses these elements, along with asolution concept of their choosing, to deduce a set of equilibriumstrategies for each player such that, when these strategies are employed, no player can profit by unilaterally deviating from their strategy. These equilibrium strategies determine anequilibrium to the game—a stable state in which either one outcome occurs or a set of outcomes occur with known probability.
Most cooperative games are presented in the characteristic function form, while the extensive and the normal forms are used to define noncooperative games.
The extensive form can be used to formalize games with a time sequencing of moves. Extensive form games can be visualized using gametrees (as pictured here). Here eachvertex (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. The extensive form can be viewed as a multi-player generalization of adecision tree.[49] To solve any extensive form game,backward induction must be used. It involves working backward up the game tree to determine what a rational player would do at the last vertex of the tree, what the player with the previous move would do given that the player with the last move is rational, and so on until the first vertex of the tree is reached.[50]
The game pictured consists of two players. The way this particular game is structured (i.e., with sequential decision making and perfect information),Player 1 "moves" first by choosing eitherF orU (fair or unfair). Next in the sequence,Player 2, who has now observedPlayer 1's move, can choose to play eitherA orR (accept or reject). OncePlayer 2 has made their choice, the game is considered finished and each player gets their respective payoff, represented in the image as two numbers, where the first number represents Player 1's payoff, and the second number represents Player 2's payoff. Suppose thatPlayer 1 choosesU and thenPlayer 2 choosesA:Player 1 then gets a payoff of "eight" (which in real-world terms can be interpreted in many ways, the simplest of which is in terms of money but could mean things such as eight days of vacation or eight countries conquered or even eight more opportunities to play the same game against other players) andPlayer 2 gets a payoff of "two".
The extensive form can also capture simultaneous-move games and games with imperfect information. To represent it, either a dotted line connects 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), or a closed line is drawn around them. (See example in theimperfect information section.)
The normal (or strategic form) game is usually represented by amatrix which shows the players, strategies, and payoffs (see the example to the right). More generally it can be represented by any function that associates a payoff for each player with every possible combination of actions. In the accompanying example 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 playsUp and that Player 2 playsLeft. Then Player 1 gets a payoff of 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.
Every extensive-form game has an equivalent normal-form game, however, the transformation to normal form may result in an exponential blowup in the size of the representation, making it computationally impractical.[51]
In cooperative game theory the characteristic function lists the payoff of each coalition. The origin of this formulation is in John von Neumann and Oskar Morgenstern's book.[52]
Formally, a characteristic function is a function[53] from the set of all possible coalitions of players to a set of payments, and also satisfies. The function describes how much collective payoff a set of players can gain by forming a coalition.
Alternative game representation forms are used for some subclasses of games or adjusted to the needs of interdisciplinary research.[54] In addition to classical game representations, some of the alternative representations also encode time related aspects.
As a method ofapplied mathematics, game theory has been used to study a wide variety of human and animal behaviors. It was initially developed ineconomics to understand a large collection of economic behaviors, including behaviors of firms, markets, and consumers. The first use of game-theoretic analysis was byAntoine Augustin Cournot in 1838 with his solution of theCournot duopoly. The use of game theory in the social sciences has expanded, and game theory has been applied to political, sociological, and psychological behaviors as well.[69]
Although pre-twentieth-centurynaturalists such asCharles Darwin made game-theoretic kinds of statements, the use of game-theoretic analysis in biology began withRonald Fisher's studies of animal behavior during the 1930s. This work predates the name "game theory", but it shares many important features with this field. The developments in economics were later applied to biology largely by John Maynard Smith in his 1982 bookEvolution and the Theory of Games.[70]
In addition to being used to describe, predict, and explain behavior, game theory has also been used to develop theories of ethical or normative behavior and toprescribe such behavior.[71] Ineconomics and philosophy, scholars have applied game theory to help in the understanding of good or proper behavior. Game-theoretic approaches have also been suggested in thephilosophy of language andphilosophy of science.[72] Game-theoretic arguments of this type can be found as far back asPlato.[73] An alternative version of game theory, called chemical game theory, represents the player's choices as metaphorical chemical reactant molecules called "knowlecules".[74] Chemical game theory then calculates the outcomes as equilibrium solutions to a system of chemical reactions.
The primary use of game theory is to describe andmodel how human populations behave.[citation needed] Some[who?] scholars believe that by finding the equilibria of games they can predict how actual human populations will behave when confronted with situations analogous to the game being studied. This particular view of game theory has been criticized[citation needed]. It is argued that the assumptions made by game theorists are often violated when applied to real-world situations. Game theorists usually assume players act rationally, but in practice, human rationality and/or behavior often deviates from the model of rationality as used in game theory. Game theorists respond by comparing their assumptions to those used inphysics. Thus while their assumptions do not always hold, they can treat game theory as a reasonable scientificideal akin to the models used byphysicists. However, empirical work has shown that in some classic games, such as thecentipede game,guess 2/3 of the average game, and thedictator game, people regularly do not play Nash equilibria. There is an ongoing debate regarding the importance of these experiments and whether the analysis of the experiments fully captures all aspects of the relevant situation.[b]
Some game theorists, following the work of John Maynard Smith andGeorge R. Price, have turned to evolutionary game theory in order to resolve these issues. These models presume either no rationality orbounded rationality on the part of players. Despite the name, evolutionary game theory does not necessarily presumenatural selection in the biological sense. Evolutionary game theory includes both biological as well as cultural evolution and also models of individual learning (for example,fictitious play dynamics).
Some scholars see game theory not as a predictive tool for the behavior of human beings, but as a suggestion for how people ought to behave. Since a strategy, corresponding to a Nash equilibrium of a game constitutes one'sbest response to the actions of the other players – provided they are in (the same) Nash equilibrium – playing a strategy that is part of a Nash equilibrium seems appropriate. This normative use of game theory has also come under criticism.[76]
This research usually focuses on particular sets of strategies known as"solution concepts" or "equilibria". A common assumption is that players act rationally. In non-cooperative games, the most famous of these is the Nash equilibrium. A set of strategies is a Nash equilibrium if each represents a best response to the other strategies. If all the players are playing the strategies in a Nash equilibrium, they have no unilateral incentive to deviate, since their strategy is the best they can do given what others are doing.[107][108]
The payoffs of the game are generally taken to represent theutility of individual players.
A prototypical paper on game theory in economics begins by presenting a game that is an abstraction of a particular economic situation. One or more solution concepts are chosen, and the author demonstrates which strategy sets in the presented game are equilibria of the appropriate type. Economists and business professors suggest two primary uses (noted above):descriptive andprescriptive.[71]
Game theory also has an extensive use in a specific branch or stream of economics –Managerial Economics. One important usage of it in the field of managerial economics is in analyzing strategic interactions between firms.[109] For example, firms may be competing in a market with limited resources, and game theory can help managers understand how their decisions impact their competitors and the overall market outcomes. Game theory can also be used to analyze cooperation between firms, such as in forming strategic alliances or joint ventures. Another use of game theory in managerial economics is in analyzing pricing strategies. For example, firms may use game theory to determine the optimalpricing strategy based on how they expect their competitors to respond to their pricing decisions. Overall, game theory serves as a useful tool for analyzing strategic interactions and decision making in the context of managerial economics.
TheChartered Institute of Procurement & Supply (CIPS) promotes knowledge and use of game theory within the context of businessprocurement.[110] CIPS and TWS Partners have conducted a series of surveys designed to explore the understanding, awareness and application of game theory amongprocurement professionals. Some of the main findings in their third annual survey (2019) include:
application of game theory to procurement activity has increased – at the time it was at 19% across all survey respondents
65% of participants predict that use of game theory applications will grow
70% of respondents say that they have "only a basic or a below basic understanding" of game theory
Sensible decision-making is critical for the success of projects. In project management, game theory is used to model the decision-making process of players, such as investors, project managers, contractors, sub-contractors, governments and customers. Quite often, these players have competing interests, and sometimes their interests are directly detrimental to other players, making project management scenarios well-suited to be modeled by game theory.
Piraveenan (2019)[112] in his review provides several examples where game theory is used to model project management scenarios. For instance, an investor typically has several investment options, and each option will likely result in a different project, and thus one of the investment options has to be chosen before the project charter can be produced. Similarly, any large project involving subcontractors, for instance, a construction project, has a complex interplay between the main contractor (the project manager) and subcontractors, or among the subcontractors themselves, which typically has several decision points. For example, if there is an ambiguity in the contract between the contractor and subcontractor, each must decide how hard to push their case without jeopardizing the whole project, and thus their own stake in it. Similarly, when projects from competing organizations are launched, the marketing personnel have to decide what is the best timing and strategy to market the project, or its resultant product or service, so that it can gain maximum traction in the face of competition. In each of these scenarios, the required decisions depend on the decisions of other players who, in some way, have competing interests to the interests of the decision-maker, and thus can ideally be modeled using game theory.
Piraveenan[112] summarizes that two-player games are predominantly used to model project management scenarios, and based on the identity of these players, five distinct types of games are used in project management.
In terms of types of games, both cooperative as well as non-cooperative, normal-form as well as extensive-form, and zero-sum as well as non-zero-sum are used to model various project management scenarios.
Early examples of game theory applied to political science are provided byAnthony Downs. In his 1957 bookAn Economic Theory of Democracy,[114] he applies theHotelling firm location model to the political process. In the Downsian model, political candidates commit to ideologies on a one-dimensional policy space. Downs first shows how the political candidates will converge to the ideology preferred by the median voter if voters are fully informed, but then argues that voters choose to remain rationally ignorant which allows for candidate divergence. Game theory was applied in 1962 to theCuban Missile Crisis during the presidency of John F. Kennedy.[115]
It has also been proposed that game theory explains the stability of any form of political government. Taking the simplest case of a monarchy, for example, the king, being only one person, does not and cannot maintain his authority by personally exercising physical control over all or even any significant number of his subjects. Sovereign control is instead explained by the recognition by each citizen that all other citizens expect each other to view the king (or other established government) as the person whose orders will be followed. Coordinating communication among citizens to replace the sovereign is effectively barred, since conspiracy to replace the sovereign is generally punishable as a crime.[116] Thus, in a process that can be modeled by variants of the prisoner's dilemma, during periods of stability no citizen will find it rational to move to replace the sovereign, even if all the citizens know they would be better off if they were all to act collectively.[citation needed]
A game-theoretic explanation fordemocratic peace is that public and open debate in democracies sends clear and reliable information regarding their intentions to other states. In contrast, it is difficult to know the intentions of nondemocratic leaders, what effect concessions will have, and if promises will be kept. Thus there will be mistrust and unwillingness to make concessions if at least one of the parties in a dispute is a non-democracy.[117]
However, game theory predicts that two countries may still go to war even if their leaders are cognizant of the costs of fighting. War may result from asymmetric information; two countries may have incentives to mis-represent the amount of military resources they have on hand, rendering them unable to settle disputes agreeably without resorting to fighting. Moreover, war may arise because of commitment problems: if two countries wish to settle a dispute via peaceful means, but each wishes to go back on the terms of that settlement, they may have no choice but to resort to warfare. Finally, war may result from issue indivisibilities.[118]
Game theory could also help predict a nation's responses when there is a new rule or law to be applied to that nation. One example is Peter John Wood's (2013) research looking into what nations could do to help reduce climate change. Wood thought this could be accomplished by making treaties with other nations to reducegreenhouse gas emissions. However, he concluded that this idea could not work because it would create a prisoner's dilemma for the nations.[119]
Game theory has been used extensively to model decision-making scenarios relevant to defence applications.[120] Most studies that has applied game theory in defence settings are concerned with Command and Control Warfare, and can be further classified into studies dealing with (i) Resource Allocation Warfare (ii) Information Warfare (iii) Weapons Control Warfare, and (iv) Adversary Monitoring Warfare.[120] Many of the problems studied are concerned with sensing and tracking, for example a surface ship trying to track a hostile submarine and the submarine trying to evade being tracked, and the interdependent decision making that takes place with regards to bearing, speed, and the sensor technology activated by both vessels.
The tool,[121] for example, automates the transformation of public vulnerability data into models, allowing defenders to synthesize optimal defence strategies through Stackelberg equilibrium analysis. This approach enhances cyber resilience by enabling defenders to anticipate and counteract attackers’ best responses, making game theory increasingly relevant in adversarial cybersecurity environments.
Ho et al. provide a broad summary of game theory applications in defence, highlighting its advantages and limitations across both physical and cyber domains.
Unlike those in economics, the payoffs for games inbiology are often interpreted as corresponding tofitness. In addition, the focus has been less on equilibria that correspond to a notion of rationality and more on ones that would be maintained by evolutionary forces. The best-known equilibrium in biology is known as theevolutionarily stable strategy (ESS), first introduced in (Maynard Smith & Price 1973). Although its initial motivation did not involve any of the mental requirements of the Nash equilibrium, every ESS is a Nash equilibrium.
In biology, game theory has been used as a model to understand many different phenomena. It was first used to explain the evolution (and stability) of the approximate 1:1sex ratios. (Fisher 1930) suggested that the 1:1 sex ratios are a result of evolutionary forces acting on individuals who could be seen as trying to maximize their number of grandchildren.
Additionally, biologists have used evolutionary game theory and the ESS to explain the emergence ofanimal communication.[122] The analysis ofsignaling games andother communication games has provided insight into the evolution of communication among animals. For example, themobbing behavior of many species, in which a large number of prey animals attack a larger predator, seems to be an example of spontaneous emergent organization. Ants have also been shown to exhibit feed-forward behavior akin to fashion (seePaul Ormerod'sButterfly Economics).
Biologists have used thegame of chicken to analyze fighting behavior and territoriality.[123]
According to Maynard Smith, in the preface toEvolution and the Theory of Games, "paradoxically, it has turned out that game theory is more readily applied to biology than to the field of economic behaviour for which it was originally designed". Evolutionary game theory has been used to explain many seemingly incongruous phenomena in nature.[124]
One such phenomenon is known asbiological altruism. This is a situation in which an organism appears to act in a way that benefits other organisms and is detrimental to itself. This is distinct from traditional notions of altruism because such actions are not conscious, but appear to be evolutionary adaptations to increase overall fitness. Examples can be found in species ranging from vampire bats that regurgitate blood they have obtained from a night's hunting and give it to group members who have failed to feed, to worker bees that care for the queen bee for their entire lives and never mate, tovervet monkeys that warn group members of a predator's approach, even when it endangers that individual's chance of survival.[125] All of these actions increase the overall fitness of a group, but occur at a cost to the individual.
Evolutionary game theory explains this altruism with the idea ofkin selection. Altruists discriminate between the individuals they help and favor relatives.Hamilton's rule explains the evolutionary rationale behind this selection with the equationc < b × r, where the costc to the altruist must be less than the benefitb to the recipient multiplied by the coefficient of relatednessr. The more closely related two organisms are causes the incidences of altruism to increase because they share many of the same alleles. This means that the altruistic individual, by ensuring that the alleles of its close relative are passed on through survival of its offspring, can forgo the option of having offspring itself because the same number of alleles are passed on. For example, helping a sibling (in diploid animals) has a coefficient of1⁄2, because (on average) an individual shares half of the alleles in its sibling's offspring. Ensuring that enough of a sibling's offspring survive to adulthood precludes the necessity of the altruistic individual producing offspring.[125] The coefficient values depend heavily on the scope of the playing field; for example if the choice of whom to favor includes all genetic living things, not just all relatives, we assume the discrepancy between all humans only accounts for approximately 1% of the diversity in the playing field, a coefficient that was1⁄2 in the smaller field becomes 0.995. Similarly if it is considered that information other than that of a genetic nature (e.g. epigenetics, religion, science, etc.) persisted through time the playing field becomes larger still, and the discrepancies smaller.
Game theory has multiple applications in the field of artificial intelligence and machine learning. It is often used in developing autonomous systems that can make complex decisions in uncertain environment.[131] Some other areas of application of game theory in AI/ML context are as follows - multi-agent system formation, reinforcement learning,[132] mechanism design etc.[133] By using game theory to model the behavior of other agents and anticipate their actions, AI/ML systems can make better decisions and operate more effectively.[134]
Game theory has been put to several uses inphilosophy. Responding to two papers byW.V.O. Quine (1960,1967),Lewis (1969) used game theory to develop a philosophical account ofconvention. In so doing, he provided the first analysis ofcommon knowledge and employed it in analyzing play incoordination games. In addition, he first suggested that one can understandmeaning in terms ofsignaling games. This later suggestion has been pursued by several philosophers since Lewis.[135][136] FollowingLewis (1969) game-theoretic account of conventions,Edna Ullmann-Margalit (1977) andBicchieri (2006) have developed theories ofsocial norms that define them as Nash equilibria that result from transforming a mixed-motive game into a coordination game.[137][138]
Game theory has also challenged philosophers to think in terms of interactiveepistemology: what it means for a collective to have common beliefs or knowledge, and what are the consequences of this knowledge for the social outcomes resulting from the interactions of agents. Philosophers who have worked in this area include Bicchieri (1989, 1993),[139][140]Skyrms (1990),[141] andStalnaker (1999).[142]
The synthesis of game theory withethics was championed byR. B. Braithwaite.[143] The hope was that rigorous mathematical analysis of game theory might help formalize the more imprecise philosophical discussions. However, this expectation was only materialized to a limited extent.[144]
Inethics, some (most notably David Gauthier, Gregory Kavka, and Jean Hampton)[who?] authors have attempted to pursueThomas Hobbes' project of deriving morality from self-interest. Since games like theprisoner's dilemma present an apparent conflict between morality and self-interest, explaining why cooperation is required by self-interest is an important component of this project. This general strategy is a component of the generalsocial contract view inpolitical philosophy (for examples, seeGauthier (1986) andKavka (1986)).[d]
Other authors have attempted to use evolutionary game theory in order to explain the emergence of human attitudes about morality and corresponding animal behaviors. These authors look at several games including the prisoner's dilemma,stag hunt, and theNash bargaining game as providing an explanation for the emergence of attitudes about morality (see, e.g., Skyrms (1996,2004) and Sober and Wilson (1998)).
Since the decision to take a vaccine for a particular disease is often made by individuals, who may consider a range of factors and parameters in making this decision (such as the incidence and prevalence of the disease, perceived and real risks associated with contracting the disease, mortality rate, perceived and real risks associated with vaccination, and financial cost of vaccination), game theory has been used to model and predict vaccination uptake in a society.[145][146]
Two members of a criminal gang, A and B, are arrested and imprisoned. Each prisoner is in solitary confinement with no means of communication with their partner. The principal charge would lead to a sentence of ten years in prison; however, the police do not have the evidence for a conviction. They plan to sentence both to two years in prison on a lesser charge but offer each prisoner a Faustian bargain: If one of them confesses to the crime of the principal charge, betraying the other, they will be pardoned and free to leave while the other must serve the entirety of the sentence instead of just two years for the lesser charge.
Thedominant strategy (and therefore the best response to any possible opponent strategy), is to betray the other, which aligns with thesure-thing principle.[148] However, both prisoners staying silent would yield a greater reward for both of them than mutual betrayal.
Battle of sexes (note they both want to do the same action but have different preferences)
The "battle of the sexes" is a term used to describe the perceived conflict between men and women in various areas of life, such as relationships, careers, and social roles. This conflict is often portrayed in popular culture, such as movies and television shows, as a humorous or dramatic competition between the genders. This conflict can be depicted in a game theory framework. This is an example of non-cooperative games.
An example of the "battle of the sexes" can be seen in the portrayal of relationships in popular media, where men and women are often depicted as being fundamentally different and in conflict with each other. For instance, in some romantic comedies, the male and female protagonists are shown as having opposing views on love and relationships, and they have to overcome these differences in order to be together.[149]
In this game, there are two pure strategy Nash equilibria: one where both the players choose the same strategy and the other where the players choose different options. If the game is played in mixed strategies, where each player chooses their strategy randomly, then there is an infinite number of Nash equilibria. However, in the context of the "battle of the sexes" game, the assumption is usually made that the game is played in pure strategies.[150]
The ultimatum game is a game that has become a popular instrument ofeconomic experiments. An early description is by Nobel laureateJohn Harsanyi in 1961.[151]
One player, the proposer, is endowed with a sum of money. The proposer is tasked with splitting it with another player, the responder (who knows what the total sum is). Once the proposer communicates his decision, the responder may accept it or reject it. If the responder accepts, the money is split per the proposal; if the responder rejects, both players receive nothing. Both players know in advance the consequences of the responder accepting or rejecting the offer. The game demonstrates how social acceptance, fairness, and generosity influence the players decisions.[152]
Ultimatum game has a variant, that is the dictator game. They are mostly identical, except in dictator game the responder has no power to reject the proposer's offer.
The Trust Game is an experiment designed to measure trust in economic decisions. It is also called "the investment game" and is designed to investigate trust and demonstrate its importance rather than "rationality" of self-interest. The game was designed by Berg Joyce, John Dickhaut and Kevin McCabe in 1995.[153]
In the game, one player (the investor) is given a sum of money and must decide how much of it to give to another player (the trustee). The amount given is then tripled by the experimenter. The trustee then decides how much of the tripled amount to return to the investor. If the trustee is completely self-interested, then they would return nothing. However, experiments have shown that this isn't the expected behavior of the trustee. The outcome instead suggests that people are willing to place trust, by risking some amount of money, in the belief that there will be reciprocity.[154]
The Cournot competition model involves players choosing quantity of a homogenous product to produce independently and simultaneously, wheremarginal cost can be different for each firm and the firm's payoff is profit. The production costs are public information and the firm aims to find their profit-maximizing quantity based on what they believe the other firm will produce and behave like monopolies. In this game firms want to produce at the monopoly quantity but there is a high incentive to deviate and produce more, which decreases the market-clearing price.[23] For example, firms may be tempted to deviate from the monopoly quantity if there is a low monopoly quantity and high price, with the aim of increasing production to maximize profit.[23] However this option does not provide the highest payoff, as a firm's ability to maximize profits depends on its market share and the elasticity of the market demand.[155] The Cournot equilibrium is reached when each firm operates on their reaction function with no incentive to deviate, as they have the best response based on the other firms output.[23] Within the game, firms reach the Nash equilibrium when the Cournot equilibrium is achieved.
The Bertrand competition assumes homogenous products and a constant marginal cost and players choose the prices.[23] The equilibrium of price competition is where the price is equal to marginal costs, assuming complete information about the competitors' costs. Therefore, the firms have an incentive to deviate from the equilibrium because a homogenous product with a lower price will gain all of the market share, known as a cost advantage.[156]
The 1964 filmDr. Strangelove satirizes game theoretic ideas aboutdeterrence theory. For example, nuclear deterrence depends on the threat to retaliate catastrophically if a nuclear attack is detected. A game theorist might argue that such threats can fail to becredible, in the sense that they can lead to subgame imperfect equilibria. The movie takes this idea one step further, with the Soviet Union irrevocably committing to a catastrophic nuclear response without making the threat public.[160]
The 1980spower pop bandGame Theory was founded by singer/songwriterScott Miller, who described the band's name as alluding to "the study of calculating the most appropriate action given an adversary... to give yourself the minimum amount of failure".[161]
Liar Game, a 2005 Japanesemanga and 2007 television series, presents the main characters in each episode with a game or problem that is typically drawn from game theory, as demonstrated by the strategies applied by the characters.[162]
The 1974 novelSpy Story byLen Deighton explores elements of game theory in regard to cold war army exercises.
The 2008 novelThe Dark Forest byLiu Cixin explores the relationship between extraterrestrial life, humanity, and game theory.
Joker, the prime antagonist in the 2008 filmThe Dark Knight presents game theory concepts—notably theprisoner's dilemma in a scene where he asks passengers in two different ferries to bomb the other one to save their own.
In the 2018 filmCrazy Rich Asians, the female lead Rachel Chu is a professor of economics and game theory atNew York University. At the beginning of the film she is seen in her NYU classroom playing a game of poker with her teaching assistant and wins the game bybluffing;[163] then in theclimax of the film, she plays a game ofmahjong with her boyfriend's disapproving mother Eleanor, losing the game to Eleanor on purpose but winning her approval as a result.[164]
In the 2017 filmMolly's Game, Brad, an inexperienced poker player, makes an irrational betting decision without realizing and causes his opponent Harlan to deviate from his Nash Equilibrium strategy, resulting in a significant loss when Harlan loses the hand.[165]
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Wikimedia Commons has media related toGame theory.
Ben-David, S.; Borodin, A.; Karp, R.; Tardos, G.; Wigderson, A. (January 1994). "On the power of randomization in on-line algorithms".Algorithmica.11 (1):2–14.doi:10.1007/BF01294260.S2CID26771869.
Skyrms, Brian (1996),Evolution of the social contract, Cambridge University Press,ISBN978-0-521-55583-8
Skyrms, Brian (2004),The stag hunt and the evolution of social structure, Cambridge University Press,ISBN978-0-521-53392-8
Sober, Elliott; Wilson, David Sloan (1998),Unto others: the evolution and psychology of unselfish behavior, Harvard University Press,ISBN978-0-674-93047-6
Webb, James N. (2007),Game theory: decisions, interaction and evolution, Undergraduate mathematics, Springer,ISBN978-1-84628-423-6 Consistent treatment of game types usually claimed by different applied fields, e.g.Markov decision processes.
Dutta, Prajit K. (1999),Strategies and games: theory and practice,MIT Press,ISBN978-0-262-04169-0. Suitable for undergraduate and business students.
Fernandez, L F.; Bierman, H S. (1998),Game theory with economic applications,Addison-Wesley,ISBN978-0-201-84758-1. Suitable for upper-level undergraduates.
Gaffal, Margit; Padilla Gálvez, Jesús (2014).Dynamics of Rational Negotiation: Game Theory, Language Games and Forms of Life. Springer.
Gibbons, Robert D. (1992),Game theory for applied economists, Princeton University Press,ISBN978-0-691-00395-5. Suitable for advanced undergraduates.
Published in Europe asGibbons, Robert (2001),A Primer in Game Theory, London: Harvester Wheatsheaf,ISBN978-0-7450-1159-2.
Gintis, Herbert (2000),Game theory evolving: a problem-centered introduction to modeling strategic behavior, Princeton University Press,ISBN978-0-691-00943-8
Joseph E. Harrington (2008)Games, strategies, and decision making, Worth,ISBN0-7167-6630-2. Textbook suitable for undergraduates in applied fields; numerous examples, fewer formalisms in concept presentation.
Miller, James H. (2003),Game theory at work: how to use game theory to outthink and outmaneuver your competition, New York:McGraw-Hill,ISBN978-0-07-140020-6. Suitable for a general audience.
reprinted edition:R. Duncan Luce; Howard Raiffa (1989),Games and decisions: introduction and critical survey, New York:Dover Publications,ISBN978-0-486-65943-5
von Neumann, John (1928), "Zur Theorie der Gesellschaftsspiele",Mathematische Annalen,100 (1):295–320,Bibcode:1928MatAn.100..295V,doi:10.1007/bf01448847,S2CID122961988 English translation: "On the Theory of Games of Strategy," in A. W. Tucker and R. D. Luce, ed. (1959),Contributions to the Theory of Games, v. 4, p.42. Princeton University Press.
Zermelo, Ernst (1913), "Über eine Anwendung der Mengenlehre auf die Theorie des Schachspiels",Proceedings of the Fifth International Congress of Mathematicians,2:501–4
