Generalized game theory

Last updated

Generalized game theory is an extension of game theory incorporating social theory concepts such as norm, value, belief, role, social relationship, and institution. The theory was developed by Tom R. Burns, Anna Gomolinska, and Ewa Roszkowska but has not had great influence beyond these immediate associates. The theory seeks to address certain perceived limitations of game theory by formulating a theory of rules and rule complexes and to develop a more robust approach to socio-psychological and sociological phenomena.

Contents

Overview

In generalized game theory, games are conceptualized as rule complexes, which is a set containing rules and/or other rule complexes. However, the rules may be imprecise, inconsistent, and even dynamic. Distinctions in the properties and functions of different types of rules allows the rules themselves to be analyzed in complex ways, and thus the models of the theory more closely represent relationships and institutions investigated in the social sciences.

The ways in which the rules may be changed is developed within the context of generalized game theory based on the principle of rule revision and game restructuring. These types of games are referred to as open games, that is, games which are open to transformation. Games which have specified, fixed players, fixed preference structures, fixed optimization procedures, and fixed action alternatives and outcomes are called closed games (characteristic of most classical game theory models).

Because its premises derive from social theory generalized game theory emphasizes and provides cultural and institutional tools for game conceptualization and analysis, [1] what Granovetter (1985) refers to as the social embeddedness of interaction and social and economic processes. [2] This is in contrast to conceptualization of games consisting of actors which are autonomous utility maximizers. Further, the modeling of the actors themselves in generalized game theory is especially open to the use of concepts such as incomplete information and bounded rationality.

Proponents of generalized game theory have advocated the application of the theory to reconceptualizing individual and collective decision-making, resolutions of the prisoners' dilemma game, agent-based modeling, fuzzy games, conflict resolution procedures, challenging and providing robust and normatively grounded alternatives to Nash equilibrium and Pareto optimality, among others.

Principles

Judgment in generalized game theory

A key aspect of actors decision making in generalized game theory is based on the concept of judgment. Several types of judgment could be relevant, for instance value judgment, factual judgment, and action judgment. In the case of action judgment, the actor seeks to take the course of action offered by the rules of the game which most closely fit the values held by the actor (where the values are a sub-rule complex of the game).

Predicting how actors will react under these sub-rules is hypothesised to be more accurate than forming traditional game theory complexes. Armstrong (2002) found that when actors hold differing beliefs and roles within a sub-game formal game theory Nash equilibriums became less reliable (it should be noted generalised game theory has received less scrutiny due to lack of notoriety). [3]

Even the method by which the actor calculates closeness of fit can be controlled by the actors values (such as an actor might use a more speedy algorithm, or a more far-sighted one). Each actor has a judgment operator by which the actor can create a preference order of the perceived qualities of possible outcomes based on satisfying the condition that the qualities of the outcomes can be roughly said to be sufficiently similar to the qualities of the actors primary values or norms. Thus, in generalized game theory, each actor's judgment calculus includes the institutional context of the game. [4]

General game solutions

A general or common game solution is a strategy or interaction order for the agents which satisfies or realizes the relevant norms and values of the players. This should lead to a state that is acceptable by the game players, and is not necessarily a normative equilibrium, but represents the "best result attainable under the circumstances". [4]

Solutions may be reached through a sequence of proposed alternatives, and when the actors find the ultimate solution acceptable, the proposed solutions may be said to be convergent. Roszkowska and Burns (2005) showed that not every game has a common solution, and that divergent proposals may arise. [5] This may result in a no equilibrium being found, and stems from dropping the assumption for the existence of a Nash equilibrium that the game be finite or that the game have complete information. Another possibility is the existence of a rule which allows a dictator to force an equilibrium. The rules which make up the norms of the game are one way of resolving the problem of choosing between multiple equilibria, such as those arising in the so-called folk theorem.

Generalization

Generalization in psychological terms is the measure of how a theory holds up when applied in a non-experimental environment. Hence, generalised game theory takes elements from this quality and applies them to game theories. Many traditional Nash equilibriums can be applied to social and psychological interactions through generalization. [6]

When Roszkowska and Burns first discussed the notion of generalised game theory, it stemmed from a need to make game theory more applicable to the real world. Game theory being more useful in describing mathematics and economics than describing psychological phenomena. Traditional notions of best choice and optimal strategy are replaced by consequentialism and instrumental rationality when applied in less abstract contexts, such as the prisoner's dilemma, dictator game and public goods game.

In open environments actors can transform game rules to create “open games”. [7] For example, if the actors concur that the consequences of their actions aren't ideal they may introduce cooperation sub-rules when there is no one adjudicating the scenario. Depending on the differing status and dispositions of the actors, game transformation can occur to form an asymmetric set of rules resulting in a non-optimal outcome. When game theories are generalized, these uncertainty factors are accounted for in the formation of interaction patterns, but role-playing is often required to understand what optimal solutions will result.

Interaction Patterns

Different observable interaction patterns will create different normative equilibriums. [6]

Interaction patterns can involve a combination of these to form resulting value judgements for divergent or contradictory outcomes.

Example: prisoner's dilemma

In the example of the two-player prisoner's dilemma, for instance, proponents of generalized game theory are critical of the rational Nash equilibrium wherein both actors defect because rational actors, it is argued, would actually be predisposed to work out coordinating mechanisms in order to achieve optimum outcomes. Although these mechanisms are not usually included in the rules of the game, generalized game theorists argue that they do exist in real life situations.

This is because there exists in most interaction situations a social relationship between the players characterized by rules and rule complexes. This relationship may be one of, for instance, solidarity (which results in the Pareto optimal outcome), adversary (which results in the Nash equilibrium), or even hierarchy (by which one actor sacrifices their own benefits for the other's good). Some values, such as pure rivalry, are seen as nonstable because both actors would seek asymmetric gain, and thus would need to either transform the game or seek another value to attempt to satisfy.

If no communication mechanism is given (as is usual in the prisoner's dilemma), the operative social relationship between the actors is based on the actors own beliefs about the other (perhaps as another member of the human race, solidarity will be felt, or perhaps as an adversary). This illustrates the principle of game transformation, which is a key element of the theory.

Related Research Articles

Game theory is the study of mathematical models of strategic interactions among rational agents. It has applications in many fields of social science, used extensively in economics as well as in logic, systems science and computer science. Traditional game theory addressed two-person zero-sum games, in which a participant's gains or losses are exactly balanced by the losses and gains of the other participant. In the 21st century, game theory applies to a wider range of behavioral relations, and it is now an umbrella term for the science of logical decision making in humans, animals, as well as computers.

Zero-sum game is a mathematical representation in game theory and economic theory of a situation that involves two sides, where the result is an advantage for one side and an equivalent loss for the other. In other words, player one's gain is equivalent to player two's loss, with the result that the net improvement in benefit of the game is zero.

In game theory, the best response is the strategy which produces the most favorable outcome for a player, taking other players' strategies as given. The concept of a best response is central to John Nash's best-known contribution, the Nash equilibrium, the point at which each player in a game has selected the best response to the other players' strategies.

In game theory, a player's strategy is any of the options which they choose in a setting where the optimal outcome depends not only on their own actions but on the actions of others. The discipline mainly concerns the action of a player in a game affecting the behavior or actions of other players. Some examples of "games" include chess, bridge, poker, monopoly, diplomacy or battleship. A player's strategy will determine the action which the player will take at any stage of the game. In studying game theory, economists enlist a more rational lens in analyzing decisions rather than the psychological or sociological perspectives taken when analyzing relationships between decisions of two or more parties in different disciplines.

In game theory, a Bayesian game is a strategic decision-making model which assumes players have incomplete information. Players hold private information relevant to the game, meaning that the payoffs are not common knowledge. Bayesian games model the outcome of player interactions using aspects of Bayesian probability. They are notable because they allowed, for the first time in game theory, for the specification of the solutions to games with incomplete information.

In game theory, strategic dominance occurs when one strategy is better than another strategy for one player, no matter how that player's opponents may play. Many simple games can be solved using dominance. The opposite, intransitivity, occurs in games where one strategy may be better or worse than another strategy for one player, depending on how the player's opponents may play.

In game theory, a repeated game is an extensive form game that consists of a number of repetitions of some base game. The stage game is usually one of the well-studied 2-person games. Repeated games capture the idea that a player will have to take into account the impact of their current action on the future actions of other players; this impact is sometimes called their reputation. Single stage game or single shot game are names for non-repeated games.

In game theory, the outcome of a game is the ultimate result of a strategic interaction with one or more people, dependant on the choices made by all participants in a certain exchange. It represents the final payoff resulting from a set of actions that individuals can take within the context of the game. Outcomes are pivotal in determining the payoffs and expected utility for parties involved. Game theorists commonly study how the outcome of a game is determined and what factors affect it.

A Colonel Blotto game is a type of two-person constant-sum game in which the players (officers) are tasked to simultaneously distribute limited resources over several objects (battlefields). In the classic version of the game, the player devoting the most resources to a battlefield wins that battlefield, and the gain is equal to the total number of battlefields won.

In game theory, a subgame perfect equilibrium is a refinement of a Nash equilibrium used in dynamic games. A strategy profile is a subgame perfect equilibrium if it represents a Nash equilibrium of every subgame of the original game. Informally, this means that at any point in the game, the players' behavior from that point onward should represent a Nash equilibrium of the continuation game, no matter what happened before. Every finite extensive game with perfect recall has a subgame perfect equilibrium. Perfect recall is a term introduced by Harold W. Kuhn in 1953 and "equivalent to the assertion that each player is allowed by the rules of the game to remember everything he knew at previous moves and all of his choices at those moves".

Quantal response equilibrium (QRE) is a solution concept in game theory. First introduced by Richard McKelvey and Thomas Palfrey, it provides an equilibrium notion with bounded rationality. QRE is not an equilibrium refinement, and it can give significantly different results from Nash equilibrium. QRE is only defined for games with discrete strategies, although there are continuous-strategy analogues.

Social rule system theory is an attempt to formally approach different kinds of social rule systems in a unified manner. Social rules systems include institutions such as norms, laws, regulations, taboos, customs, and a variety of related concepts and are important in the social sciences and humanities. Social rule system theory is fundamentally an institutionalist approach to the social sciences, both in its placing primacy on institutions and in its use of sets of rules to define concepts in social theory.

In game theory, the traveler's dilemma is a non-zero-sum game in which each player proposes a payoff. The lower of the two proposals wins; the lowball player receives the lowball payoff plus a small bonus, and the highball player receives the same lowball payoff, minus a small penalty. Surprisingly, the Nash equilibrium is for both players to aggressively lowball. The traveler's dilemma is notable in that naive play appears to outperform the Nash equilibrium; this apparent paradox also appears in the centipede game and the finitely-iterated prisoner's dilemma.

Cooperative bargaining is a process in which two people decide how to share a surplus that they can jointly generate. In many cases, the surplus created by the two players can be shared in many ways, forcing the players to negotiate which division of payoffs to choose. Such surplus-sharing problems are faced by management and labor in the division of a firm's profit, by trade partners in the specification of the terms of trade, and more.

A rule complex is a set consisting of rules and/or other rule complexes. This is a generalization of a set of rules, and provides a tool to investigate and describe how rules can function as values, norms, judgmental or prescriptive rules, and meta-rules. Also possible is to examine objects consisting of rules such as roles, routines, algorithms, models of reality, social relationships, and institutions. In game theory, rules and rule complexes can be used to define the behavior and interactions of the players (although in generalized game theory, the rules are not necessarily static. Rule complexes are especially associated with sociologist Tom R. Burns and Anna Gomolinska and the Uppsala Theory Circle.

In algorithmic game theory, a succinct game or a succinctly representable game is a game which may be represented in a size much smaller than its normal form representation. Without placing constraints on player utilities, describing a game of players, each facing strategies, requires listing utility values. Even trivial algorithms are capable of finding a Nash equilibrium in a time polynomial in the length of such a large input. A succinct game is of polynomial type if in a game represented by a string of length n the number of players, as well as the number of strategies of each player, is bounded by a polynomial in n.

<span class="mw-page-title-main">Jean-François Mertens</span> Belgian game theorist (1946–2012)

Jean-François Mertens was a Belgian game theorist and mathematical economist.

The Berge equilibrium is a game theory solution concept named after the mathematician Claude Berge. It is similar to the standard Nash equilibrium, except that it aims to capture a type of altruism rather than purely non-cooperative play. Whereas a Nash equilibrium is a situation in which each player of a strategic game ensures that they personally will receive the highest payoff given other players' strategies, in a Berge equilibrium every player ensures that all other players will receive the highest payoff possible. Although Berge introduced the intuition for this equilibrium notion in 1957, it was only formally defined by Vladislav Iosifovich Zhukovskii in 1985, and it was not in widespread use until half a century after Berge originally developed it.

<span class="mw-page-title-main">Ferenc Forgó</span> Hungarian mathematician, economist

Ferenc Forgó (born 16 April 1942 in Pécs) is a Hungarian economist and mathematician. He is a Doctor of the Hungarian Academy of Sciences and professor emeritus at the Corvinus University of Budapest. His main research interests have been mathematical programming and game theory.

References

  1. (Baumgartner et al., 1975, see Burns, 2005)
  2. (Granovetter, 1985)
  3. Armstrong, J.Scott (2002). "Assessing game theory, role playing, and unaided judgment". International Journal of Forecasting. 18 (3): 345–352. doi:10.1016/S0169-2070(02)00024-9. ISSN   0169-2070. S2CID   2226294.
  4. 1 2 (Burns, 2005)
  5. Martin, Arnaud; Zarate, Pascale; Camillieri, Guy (2016-09-09), "A Multi-Criteria Recommender System Based on Users' Profile Management", Multiple Criteria Decision Making, Cham: Springer International Publishing, pp. 83–98, doi:10.1007/978-3-319-39292-9_5, ISBN   978-3-319-39290-5 , retrieved 2022-04-03
  6. 1 2 Burns, Tom; Roszkowska, Ewa; des Johansson, Nora Machado (2014). "Distributive Justice: From Steinhaus, Knaster, and Banach to Elster and Rawls — The Perspective of Sociological Game Theory". Studies in Logic, Grammar and Rhetoric. 37 (1): 11–38. doi:10.2478/slgr-2014-0015. hdl: 10071/8629 . ISSN   2199-6059. S2CID   144751751.
  7. Subbotin, A. I. (1984). "Generalization of the main equation of differential game theory". Journal of Optimization Theory and Applications. 43 (1): 103–133. doi:10.1007/BF00934749. ISSN   0022-3239. S2CID   121851942.

Further reading