Determinacy of Nonzero-Sum Games

Total Page:16

File Type:pdf, Size:1020Kb

Determinacy of Nonzero-Sum Games Determinacy of Nonzero-sum Games Wenzhang Zhang 1 April 4, 2008 1School of Economics, Shanghai University of Finance and Economics, Shanghai 200433, China. Email: [email protected] Abstract In this paper we study a class of infinite games with perfect information and define a new solution concept that we call determinacy for these games. We start by motivat- ing and formalizing three simple behavioral axioms about how rational players should behave in backward induction games, pure cooperation games and pure competition games, respectively. Then we say that a general game is determined if it can be solved by repeatedly applying these axioms to its subgames. This solution concept has nice properties and important implications for subgame perfect Nash equilibrium and iter- ated weak dominance. In particular, the outcome given by determinacy is a unique payoff vector that corresponds to the value of a subgame perfect Nash equilibrium. Thus determinacy can be regarded as a unique refinement of subgame perfect Nash equilibrium. Keywords: Determinacy, Backward induction, Nonzero-sum games, Infinite games of perfect information. JEL Classification: C72, C73. 1 Introduction In their pioneering study, Gale and Stewart (1953) investigate the following class of infinite games with perfect information. Two players, 1 and 2, alternate choosing elements of a set Y . First player 1 chooses y0, then player 2 chooses y1, then player 1 chooses y2, etc., so that an infinite sequence of choices (y0, y1, y2,... ) is specified. The payoffs of the players are defined by a pair of subsets A1 and A2 that form a partition of the total space of such sequences (y0, y1, y2,... ): The sets A1 and A2 are called the payoff sets of players 1 and 2, respectively, and a player wins just in case the sequence (y0, y1, y2,... ) is a member of his payoff set. So one and only one player wins in each play and these games are called zero-sum games. A winning strategy for a player is a strategy following which he always wins, re- gardless of what his opponent does. A game is called determined if one of the players has a winning strategy. Gale and Stewart prove the fundamental result that if one of the two payoff sets is closed in the natural product topology of the total space, then the game is determined. They further ask whether this is true if the payoff sets are Borel sets. This question inspires many years of study, e.g., Wolfe (1955), Davis (1964), and the seminal work of Martin (1975), which provides the final affirmative answer. These games are certainly deep and elegant objects of study. For example, they play a key role in the foundation of mathematics (see, e.g., Chapter 6 of Kanamori (2000)). Nevertheless, the requirement that the games be zero-sum is too restrictive for practical applications. For example, the games in economics are almost exclusively nonzero-sum games, with even more general payoff and information structures. The aim of this paper is to provide a general study of nonzero-sum games, that is, games in which the pair of payoff sets A1 and A2 need not be a partition of the total space. Unlike for zero-sum games, there is no obvious notion of determinacy for nonzero-sum games. Thus our first task is to define a notion of determinacy for nonzero-sum games. Our approach is axiomatic and the main steps are summarized as follows. 1 (i) We call a game trivial if each payoff set Ai is either the empty set or the total space. Thus a player in a trivial game either wins or loses for sure. We start with the observation that a trivial game can be regarded as determined since no matter how the game is played the payoffs to the players are the same. (ii) Next we consider several simple games in which it is clear what strategies rational players should follow. We propose several axioms requiring that in these games the players should follow these rational strategies. If the players follow these strategies, then each such game is equivalent to a trivial game that has the same outcome. So we let each axiom take the form that a game satisfying certain conditions can be reduced to a trivial game. (iii) Finally, we define the determinacy of a general game G by trying to reduce it to a trivial game using these axioms. Start with a subgame of G that satisfies the conditions of an axiom. We obtain a new game G1 from G by replacing this subgame by the equivalent, trivial game suggested by the axiom. Similarly we can apply the axioms to a subgame of G1 to obtain another game G2. Continuing in this manner we obtain a chain of games hG, G1,G2,...,Gni. If at certain stage we reach a trivial game Gn, then we stop and say that the game G is determined. Intuitively, a game is determined if it can be “solved” by repeatedly solving its subgames using the axioms. The focus of this paper is to describe this class of games, motivate and formalize the axioms, define determinacy, and illustrate the working of this definition. Building on these, in two companion papers (Zhang (2008a) and Zhang (2008b)), we show that the axioms are consistent, complete and independent. Specifically, we prove that: (i) If we have two such chains for a given game, then the trivial games at the end of these two chains must be the same. Therefore the axioms do not contradict each other and the definition of determinacy does not depend on the order the axioms are applied. (ii) All games with closed payoff sets are determined. Thus the axioms are complete in the sense that they are able to solve the class of games with closed payoff sets. This result is also an extension of the fundamental theorem of Gale and Stewart to nonzero-sum games. (iii) If we drop any of these axioms, then there will be a game indetermined. 2 So none of the axioms is redundant. These results have important implications for subgame perfect Nash equilibrium and iterated weak dominance. In another companion paper (Zhang (2008c)), we show that these results also enhance our understanding of these two solution concepts. For subgame perfect Nash equilibrium, we establish the following results. (i) We investigate why most games have a large number of subgame perfect Nash equilibria, and show that this multiplicity arises because Nash equilibrium is too weak. The most severe case arises in pure cooperation games in which there are common interests that require the players to cooperate to realize these common interests. Nash equilibrium always fails to give the cooperative outcomes as the only predictions. (ii) We show that the outcome given by determinacy is a unique payoff vector that corresponds to the value of a subgame perfect Nash equilibrium, and so determinacy can be regarded as a unique refinement of subgame perfect Nash equilibrium. (iii) By combining these results we are able to prove that for the class of closed games a subgame perfect Nash equilibrium always exists. For iterated weak dominance, we investigate why it is in general order dependent. We find that one prediction of weak dominance on backward induction games is too strong and this leads to the order dependence. The facts that our axioms do not have this prediction and that determinacy is order independent suggest that in order to have an order independent solution concept we have to abandon this strong and inconsistent prediction of weak dominance. The rest of this paper is organized as follows. In Section 2 we review the related literature and point out directions for further work. In Section 3 we introduce the axioms. In Section 4 we define determinacy and summarize the main results in the companion papers. In Section 5 we interpret the outcome given by determinacy, and illustrate the working of determinacy by an example and by proving that finite games are determined. For a technical reason we have to use a transfinite version of determinacy that allows us to apply the axioms infinitely many times. This is important for a general analysis, 3 but the main ideas of the definitions and the main results can be understood using the finite version. For this reason in Section 4 we use the finite version for exposition. We motivate the transfinite version of determinacy and restate the main definitions and results using this version in Section 6. We also illustrate the working of this transfinite version by solving an example. Section 7 concludes. 2 Related Literature and Further Work 2.1 Related literature In this section we briefly review the literature that are related to the results of this paper and the results mentioned in this paper but studied in detail in the companion papers. Related literature on equilibrium refinements. The notion of subgame perfect Nash equilibrium is defined in Selten (1965) and Selten (1975). Maskin and Tirole (2001) study a widely applied refinement of subgame perfect Nash equilibrium in which the players’ strategies depend only on the state variables (Markov perfect equilibrium). Our papers contribute to this literature since determinacy is a unique refinement of subgame perfect Nash equilibrium, and so it can be regarded as a realization of the refinement program in the case of infinite two-person perfect-information games with characteristic payoff functions. Moreover, the analysis in these papers improves our understanding about why most games have multiple equilibria. Related literature on the existence of subgame perfect Nash equilibrium. The exis- tence of subgame perfect Nash equilibrium in games with perfect information and with infinite horizon has been studied in several influential papers, for example, Fudenberg and Levine (1983), Harris (1985a), Harris (1985b), Harris, Reny, and Robson (1995), Hellwig and Leininger (1987), and Hellwig, Leininger, Reny, and Robson (1990).
Recommended publications
  • Game Theory 2: Extensive-Form Games and Subgame Perfection
    Game Theory 2: Extensive-Form Games and Subgame Perfection 1 / 26 Dynamics in Games How should we think of strategic interactions that occur in sequence? Who moves when? And what can they do at different points in time? How do people react to different histories? 2 / 26 Modeling Games with Dynamics Players Player function I Who moves when Terminal histories I Possible paths through the game Preferences over terminal histories 3 / 26 Strategies A strategy is a complete contingent plan Player i's strategy specifies her action choice at each point at which she could be called on to make a choice 4 / 26 An Example: International Crises Two countries (A and B) are competing over a piece of land that B occupies Country A decides whether to make a demand If Country A makes a demand, B can either acquiesce or fight a war If A does not make a demand, B keeps land (game ends) A's best outcome is Demand followed by Acquiesce, worst outcome is Demand and War B's best outcome is No Demand and worst outcome is Demand and War 5 / 26 An Example: International Crises A can choose: Demand (D) or No Demand (ND) B can choose: Fight a war (W ) or Acquiesce (A) Preferences uA(D; A) = 3 > uA(ND; A) = uA(ND; W ) = 2 > uA(D; W ) = 1 uB(ND; A) = uB(ND; W ) = 3 > uB(D; A) = 2 > uB(D; W ) = 1 How can we represent this scenario as a game (in strategic form)? 6 / 26 International Crisis Game: NE Country B WA D 1; 1 3X; 2X Country A ND 2X; 3X 2; 3X I Is there something funny here? I Is there something funny here? I Specifically, (ND; W )? I Is there something funny here?
    [Show full text]
  • Frequently Asked Questions in Mathematics
    Frequently Asked Questions in Mathematics The Sci.Math FAQ Team. Editor: Alex L´opez-Ortiz e-mail: [email protected] Contents 1 Introduction 4 1.1 Why a list of Frequently Asked Questions? . 4 1.2 Frequently Asked Questions in Mathematics? . 4 2 Fundamentals 5 2.1 Algebraic structures . 5 2.1.1 Monoids and Groups . 6 2.1.2 Rings . 7 2.1.3 Fields . 7 2.1.4 Ordering . 8 2.2 What are numbers? . 9 2.2.1 Introduction . 9 2.2.2 Construction of the Number System . 9 2.2.3 Construction of N ............................... 10 2.2.4 Construction of Z ................................ 10 2.2.5 Construction of Q ............................... 11 2.2.6 Construction of R ............................... 11 2.2.7 Construction of C ............................... 12 2.2.8 Rounding things up . 12 2.2.9 What’s next? . 12 3 Number Theory 14 3.1 Fermat’s Last Theorem . 14 3.1.1 History of Fermat’s Last Theorem . 14 3.1.2 What is the current status of FLT? . 14 3.1.3 Related Conjectures . 15 3.1.4 Did Fermat prove this theorem? . 16 3.2 Prime Numbers . 17 3.2.1 Largest known Mersenne prime . 17 3.2.2 Largest known prime . 17 3.2.3 Largest known twin primes . 18 3.2.4 Largest Fermat number with known factorization . 18 3.2.5 Algorithms to factor integer numbers . 18 3.2.6 Primality Testing . 19 3.2.7 List of record numbers . 20 3.2.8 What is the current status on Mersenne primes? .
    [Show full text]
  • Uniqueness and Symmetry in Bargaining Theories of Justice
    Philos Stud DOI 10.1007/s11098-013-0121-y Uniqueness and symmetry in bargaining theories of justice John Thrasher Ó Springer Science+Business Media Dordrecht 2013 Abstract For contractarians, justice is the result of a rational bargain. The goal is to show that the rules of justice are consistent with rationality. The two most important bargaining theories of justice are David Gauthier’s and those that use the Nash’s bargaining solution. I argue that both of these approaches are fatally undermined by their reliance on a symmetry condition. Symmetry is a substantive constraint, not an implication of rationality. I argue that using symmetry to generate uniqueness undermines the goal of bargaining theories of justice. Keywords David Gauthier Á John Nash Á John Harsanyi Á Thomas Schelling Á Bargaining Á Symmetry Throughout the last century and into this one, many philosophers modeled justice as a bargaining problem between rational agents. Even those who did not explicitly use a bargaining problem as their model, most notably Rawls, incorporated many of the concepts and techniques from bargaining theories into their understanding of what a theory of justice should look like. This allowed them to use the powerful tools of game theory to justify their various theories of distributive justice. The debates between partisans of different theories of distributive justice has tended to be over the respective benefits of each particular bargaining solution and whether or not the solution to the bargaining problem matches our pre-theoretical intuitions about justice. There is, however, a more serious problem that has effectively been ignored since economists originally J.
    [Show full text]
  • Biography Paper – Georg Cantor
    Mike Garkie Math 4010 – History of Math UCD Denver 4/1/08 Biography Paper – Georg Cantor Few mathematicians are house-hold names; perhaps only Newton and Euclid would qualify. But there is a second tier of mathematicians, those whose names might not be familiar, but whose discoveries are part of everyday math. Examples here are Napier with logarithms, Cauchy with limits and Georg Cantor (1845 – 1918) with sets. In fact, those who superficially familier with Georg Cantor probably have two impressions of the man: First, as a consequence of thinking about sets, Cantor developed a theory of the actual infinite. And second, that Cantor was a troubled genius, crippled by Freudian conflict and mental illness. The first impression is fundamentally true. Cantor almost single-handedly overturned the Aristotle’s concept of the potential infinite by developing the concept of transfinite numbers. And, even though Bolzano and Frege made significant contributions, “Set theory … is the creation of one person, Georg Cantor.” [4] The second impression is mostly false. Cantor certainly did suffer from mental illness later in his life, but the other emotional baggage assigned to him is mostly due his early biographers, particularly the infamous E.T. Bell in Men Of Mathematics [7]. In the racially charged atmosphere of 1930’s Europe, the sensational story mathematician who turned the idea of infinity on its head and went crazy in the process, probably make for good reading. The drama of the controversy over Cantor’s ideas only added spice. 1 Fortunately, modern scholars have corrected the errors and biases in older biographies.
    [Show full text]
  • Game Theory- Prisoners Dilemma Vs Battle of the Sexes EXCERPTS
    Lesson 14. Game Theory 1 Lesson 14 Game Theory c 2010, 2011 ⃝ Roberto Serrano and Allan M. Feldman All rights reserved Version C 1. Introduction In the last lesson we discussed duopoly markets in which two firms compete to sell a product. In such markets, the firms behave strategically; each firm must think about what the other firm is doing in order to decide what it should do itself. The theory of duopoly was originally developed in the 19th century, but it led to the theory of games in the 20th century. The first major book in game theory, published in 1944, was Theory of Games and Economic Behavior,byJohnvon Neumann (1903-1957) and Oskar Morgenstern (1902-1977). We will return to the contributions of Von Neumann and Morgenstern in Lesson 19, on uncertainty and expected utility. Agroupofpeople(orteams,firms,armies,countries)areinagame if their decision problems are interdependent, in the sense that the actions that all of them take influence the outcomes for everyone. Game theory is the study of games; it can also be called interactive decision theory. Many real-life interactions can be viewed as games. Obviously football, soccer, and baseball games are games.Butsoaretheinteractionsofduopolists,thepoliticalcampaignsbetweenparties before an election, and the interactions of armed forces and countries. Even some interactions between animal or plant species in nature can be modeled as games. In fact, game theory has been used in many different fields in recent decades, including economics, political science, psychology, sociology, computer science, and biology. This brief lesson is not meant to replace a formal course in game theory; it is only an in- troduction.
    [Show full text]
  • Lecture Notes
    GRADUATE GAME THEORY LECTURE NOTES BY OMER TAMUZ California Institute of Technology 2018 Acknowledgments These lecture notes are partially adapted from Osborne and Rubinstein [29], Maschler, Solan and Zamir [23], lecture notes by Federico Echenique, and slides by Daron Acemoglu and Asu Ozdaglar. I am indebted to Seo Young (Silvia) Kim and Zhuofang Li for their help in finding and correcting many errors. Any comments or suggestions are welcome. 2 Contents 1 Extensive form games with perfect information 7 1.1 Tic-Tac-Toe ........................................ 7 1.2 The Sweet Fifteen Game ................................ 7 1.3 Chess ............................................ 7 1.4 Definition of extensive form games with perfect information ........... 10 1.5 The ultimatum game .................................. 10 1.6 Equilibria ......................................... 11 1.7 The centipede game ................................... 11 1.8 Subgames and subgame perfect equilibria ...................... 13 1.9 The dollar auction .................................... 14 1.10 Backward induction, Kuhn’s Theorem and a proof of Zermelo’s Theorem ... 15 2 Strategic form games 17 2.1 Definition ......................................... 17 2.2 Nash equilibria ...................................... 17 2.3 Classical examples .................................... 17 2.4 Dominated strategies .................................. 22 2.5 Repeated elimination of dominated strategies ................... 22 2.6 Dominant strategies ..................................
    [Show full text]
  • Prisoners of Reason Game Theory and Neoliberal Political Economy
    C:/ITOOLS/WMS/CUP-NEW/6549131/WORKINGFOLDER/AMADAE/9781107064034PRE.3D iii [1–28] 11.8.2015 9:57PM Prisoners of Reason Game Theory and Neoliberal Political Economy S. M. AMADAE Massachusetts Institute of Technology C:/ITOOLS/WMS/CUP-NEW/6549131/WORKINGFOLDER/AMADAE/9781107064034PRE.3D iv [1–28] 11.8.2015 9:57PM 32 Avenue of the Americas, New York, ny 10013-2473, usa Cambridge University Press is part of the University of Cambridge. It furthers the University’s mission by disseminating knowledge in the pursuit of education, learning, and research at the highest international levels of excellence. www.cambridge.org Information on this title: www.cambridge.org/9781107671195 © S. M. Amadae 2015 This publication is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2015 Printed in the United States of America A catalog record for this publication is available from the British Library. Library of Congress Cataloging in Publication Data Amadae, S. M., author. Prisoners of reason : game theory and neoliberal political economy / S.M. Amadae. pages cm Includes bibliographical references and index. isbn 978-1-107-06403-4 (hbk. : alk. paper) – isbn 978-1-107-67119-5 (pbk. : alk. paper) 1. Game theory – Political aspects. 2. International relations. 3. Neoliberalism. 4. Social choice – Political aspects. 5. Political science – Philosophy. I. Title. hb144.a43 2015 320.01′5193 – dc23 2015020954 isbn 978-1-107-06403-4 Hardback isbn 978-1-107-67119-5 Paperback Cambridge University Press has no responsibility for the persistence or accuracy of URLs for external or third-party Internet Web sites referred to in this publication and does not guarantee that any content on such Web sites is, or will remain, accurate or appropriate.
    [Show full text]
  • Implementation Theory*
    Chapter 5 IMPLEMENTATION THEORY* ERIC MASKIN Institute for Advanced Study, Princeton, NJ, USA TOMAS SJOSTROM Department of Economics, Pennsylvania State University, University Park, PA, USA Contents Abstract 238 Keywords 238 1. Introduction 239 2. Definitions 245 3. Nash implementation 247 3.1. Definitions 248 3.2. Monotonicity and no veto power 248 3.3. Necessary and sufficient conditions 250 3.4. Weak implementation 254 3.5. Strategy-proofness and rich domains of preferences 254 3.6. Unrestricted domain of strict preferences 256 3.7. Economic environments 257 3.8. Two agent implementation 259 4. Implementation with complete information: further topics 260 4.1. Refinements of Nash equilibrium 260 4.2. Virtual implementation 264 4.3. Mixed strategies 265 4.4. Extensive form mechanisms 267 4.5. Renegotiation 269 4.6. The planner as a player 275 5. Bayesian implementation 276 5.1. Definitions 276 5.2. Closure 277 5.3. Incentive compatibility 278 5.4. Bayesian monotonicity 279 * We are grateful to Sandeep Baliga, Luis Corch6n, Matt Jackson, Byungchae Rhee, Ariel Rubinstein, Ilya Segal, Hannu Vartiainen, Masahiro Watabe, and two referees, for helpful comments. Handbook of Social Choice and Welfare, Volume 1, Edited by K.J Arrow, A.K. Sen and K. Suzumura ( 2002 Elsevier Science B. V All rights reserved 238 E. Maskin and T: Sj'str6m 5.5. Non-parametric, robust and fault tolerant implementation 281 6. Concluding remarks 281 References 282 Abstract The implementation problem is the problem of designing a mechanism (game form) such that the equilibrium outcomes satisfy a criterion of social optimality embodied in a social choice rule.
    [Show full text]
  • Repeated Games
    REPEATED GAMES 1 Early PD experiments In 1950, Merrill Flood and Melvin Dresher (at RAND) devised an experiment to test Nash’s theory about defection in a two-person prisoners’ dilemma. Experimental Design – They asked two friends to play the PD 100 times. – They measured the success of Nash’s equilibrium concept by counting the number of times the players chose {D;D}. 2 Flood and Dresher’s results Player 1 cooperated in 68 rounds Player 2 cooperated in 78 rounds Both cooperated in 60 of last 89 rounds Flood Dresher Nash 3 Flood and Dresher’s results Player 1 cooperated in 68 rounds Player 2 cooperated in 78 rounds Both cooperated in 60 of last 89 rounds Wait a Ha! That jerk I can’tI’mOh a be Ha! Nash second... Nash was genius...%&@#!wrong! was wrong! wrong! Flood Dresher Nash 4 Nash’s response “If this experiment were conducted with various different players rotating the competition and with no information given to a player of what choices the others have been making until the end of all trials, then the experimental results would have been quite different, for this modification of procedure would remove the interaction between the trials.” 5 Nash’s response “The flaw in this experiment as a test of equilibrium point theory is that the experiment really amounts to having the players play one large multimove game. One cannot...think of the thing as a sequence of independent games...there is too much interaction.” In other words, Nash said that repeating the game changes the game itself.
    [Show full text]
  • Collusion Constrained Equilibrium
    Theoretical Economics 13 (2018), 307–340 1555-7561/20180307 Collusion constrained equilibrium Rohan Dutta Department of Economics, McGill University David K. Levine Department of Economics, European University Institute and Department of Economics, Washington University in Saint Louis Salvatore Modica Department of Economics, Università di Palermo We study collusion within groups in noncooperative games. The primitives are the preferences of the players, their assignment to nonoverlapping groups, and the goals of the groups. Our notion of collusion is that a group coordinates the play of its members among different incentive compatible plans to best achieve its goals. Unfortunately, equilibria that meet this requirement need not exist. We instead introduce the weaker notion of collusion constrained equilibrium. This al- lows groups to put positive probability on alternatives that are suboptimal for the group in certain razor’s edge cases where the set of incentive compatible plans changes discontinuously. These collusion constrained equilibria exist and are a subset of the correlated equilibria of the underlying game. We examine four per- turbations of the underlying game. In each case,we show that equilibria in which groups choose the best alternative exist and that limits of these equilibria lead to collusion constrained equilibria. We also show that for a sufficiently broad class of perturbations, every collusion constrained equilibrium arises as such a limit. We give an application to a voter participation game that shows how collusion constraints may be socially costly. Keywords. Collusion, organization, group. JEL classification. C72, D70. 1. Introduction As the literature on collective action (for example, Olson 1965) emphasizes, groups often behave collusively while the preferences of individual group members limit the possi- Rohan Dutta: [email protected] David K.
    [Show full text]
  • Subgame-Perfect Ε-Equilibria in Perfect Information Games With
    Subgame-Perfect -Equilibria in Perfect Information Games with Common Preferences at the Limit Citation for published version (APA): Flesch, J., & Predtetchinski, A. (2016). Subgame-Perfect -Equilibria in Perfect Information Games with Common Preferences at the Limit. Mathematics of Operations Research, 41(4), 1208-1221. https://doi.org/10.1287/moor.2015.0774 Document status and date: Published: 01/11/2016 DOI: 10.1287/moor.2015.0774 Document Version: Publisher's PDF, also known as Version of record Document license: Taverne Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.
    [Show full text]
  • Nash Equilibrium
    Lecture 3: Nash equilibrium Nash equilibrium: The mathematician John Nash introduced the concept of an equi- librium for a game, and equilibrium is often called a Nash equilibrium. They provide a way to identify reasonable outcomes when an easy argument based on domination (like in the prisoner's dilemma, see lecture 2) is not available. We formulate the concept of an equilibrium for a two player game with respective 0 payoff matrices PR and PC . We write PR(s; s ) for the payoff for player R when R plays 0 s and C plays s, this is simply the (s; s ) entry the matrix PR. Definition 1. A pair of strategies (^sR; s^C ) is an Nash equilbrium for a two player game if no player can improve his payoff by changing his strategy from his equilibrium strategy to another strategy provided his opponent keeps his equilibrium strategy. In terms of the payoffs matrices this means that PR(sR; s^C ) ≤ P (^sR; s^C ) for all sR ; and PC (^sR; sC ) ≤ P (^sR; s^C ) for all sc : The idea at work in the definition of Nash equilibrium deserves a name: Definition 2. A strategy s^R is a best-response to a strategy sc if PR(sR; sC ) ≤ P (^sR; sC ) for all sR ; i.e. s^R is such that max PR(sR; sC ) = P (^sR; sC ) sR We can now reformulate the idea of a Nash equilibrium as The pair (^sR; s^C ) is a Nash equilibrium if and only ifs ^R is a best-response tos ^C and s^C is a best-response tos ^R.
    [Show full text]