DOCSLIB.ORG

The Electronic Mail Game: Strategic Behavior Under" Almost Common Knowledge"

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The Electronic Mail Game: Strategic Behavior Under See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/4719889 The Electronic Mail Game: Strategic Behavior Under" Almost Common Knowledge" Article in American Economic Review · February 1989 Source: RePEc CITATIONS READS 294 1,780 1 author: Ariel Rubinstein Tel Aviv University 178 PUBLICATIONS 18,904 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: With any requests please contact me directly [email protected] View project Procedures of Decision Making as Revealed through Eye Movements View project All content following this page was uploaded by Ariel Rubinstein on 23 February 2014. The user has requested enhancement of the downloaded file. The Electronic Mail Game: Strategic Behavior Under "Almost Common Knowledge" Ariel Rubinstein The American Economic Review, Vol. 79, No. 3. (Jun., 1989), pp. 385-391. Stable URL: http://links.jstor.org/sici?sici=0002-8282%28198906%2979%3A3%3C385%3ATEMGSB%3E2.0.CO%3B2-U The American Economic Review is currently published by American Economic Association. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/journals/aea.html. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. The JSTOR Archive is a trusted digital repository providing for long-term preservation and access to leading academic journals and scholarly literature from around the world. The Archive is supported by libraries, scholarly societies, publishers, and foundations. It is an initiative of JSTOR, a not-for-profit organization with a mission to help the scholarly community take advantage of advances in technology. For more information regarding JSTOR, please contact [email protected]. http://www.jstor.org Thu Mar 27 12:47:26 2008 The Electronic Mail Game: Strategic Behavior Under "Almost Common Knowledge" The paper addresses a paradoxical game-theoretic example which is closely related to the coordinated attack problem. Two players have to play one of two possible coordination games. Only one of them receives information about the coordination game to be played. It is shown that the situation with "almost common knowledge" is very diferent from when the coordination game played is common knowledge. A very basic assumption in all studies (for a recent presentation of this literature of game theory is that the game is "com- see Ken Binmore and Adam Brandenberger, mon knowledge." Following John Harsanyi 1987). Intuitively speaking it is common (1967), situations without common knowl- knowledge between two players 1 and 2 that edge are analyzed by a game with incom- the played game is G, if both know that the plete information. A player's information is game is G, 1 knows that 2 knows that the characterized by his "type." Each player game is G and 2 knows that 1 knows that "knows" his own type and the prior distri- the game is G, 1knows that 2 knows that 1 bution of the types is common knowledge. knows that the game is G, and 2 knows that Jean-Francois Mertens and Samuel Zamir 1 knows that 2 knows that the game is G (1985) have shown that under quite general and so on and so on. conditions one can find type spaces large One of the main difficulties with this intu- enough to carry out Harsanyi's program and itive definition (and with the formal defini- to transform a situation without common tions which capture this perception) is that knowledge into a gaine with incomplete in- even "simple" sentences like "I do not know formation in which the different types may that you do not know that I know that you have different states of knowledge. Har- do not know that I know" are very difficult sanyi's method became the cornerstone of all to visualize, thus malung an assessment of modem analyses of strategic economic be- their validity problematic. Therefore it would havior in situations with asymmetric infor- be interesting to understand whether a mation (i.e., most of the theoretical Indus- game-theoretic informational structure, re- trial Organization literature). ferred to as "almost common knowledge," in What does it mean that the game G is which only a finite (but large) number of "common knowledge"? Following David propositions of the type "1 knows that 2 Lewis (1969), Stephen Schiffer (1972), and knows that 1 knows.. .that the game is G" Robert Aumann (1976), this concept has are true, is very different from the situation been studied thoroughly by relating it to where the game G is common knowledge. In concepts of "knowledge" and "probability" this short paper I will present a simple ex- ample of a situation with "almost common knowledge" of the game. The situation is analyzed using, as a tool, the idea of a game *Department of Economics, The Hebrew University, with incomplete information. It is shown Jerusalem, and the London School of Economics, that the game-theoretic "prediction" for the Houghton Street, London, England W02A2AE. My thanks to Ken Binmore, Edi Dekel, John Geanakopo- "almost common knowledge" situation is los, Avner Shaked, Chuck Wilson, Asher Wolinsky, and very different from the situation with com- a referee of this journal for the very useful comments. mon knowledge. 386 THE AMERICAN ECONOMIC RE VIEW JUNE 1989 The example is similar to the "coordi- cannot achieve an expected payoff hgher nated attack problem" which is well known than (1 - p)M. If the information could be- in the distributed systems literature.' A come common knowledge they would be able description of the problem and a compari- to achieve the payoff M. However, imagine son with ths paper analyzed appears in Sec- that the two players are located at two dif- tion IV. ferent sites and they communicate only by electronic mail signals. Due to "technical 1. Coordination Through Electronic Mail difficulties" there is a "small" probability E > 0,that the message does not arrive at its Two players, 1 and 2, are involved in a destination. At the risk of creating discord, coordination problem. Each has to choose the electronic mail network is set up to send between two actions A and B. There are two a confirmation automatically if any message possible states of nature, a and b. Each of is received, including not only the confirma- the states is associated with a payoff matrix tion of the initial message but a confirmation as follows: of the confirmation; and so on. To be more precise, it is assumed that, when player 1 gets the information that the state of nature The game G, is b, hs computer automatically sends a A B message (a blip) to player 2 and then player A M, M 0,- L 2's computer confirms the message and then B - L,O 090 player 1's computer confirms the confirma- tion and so on. If a message does not arrive, state a then the communication stops. No message probability 1- p is sent if the state of nature is a. At the end of the communication phase the screen dis- The game G, plays to the player the number of messages A B his machne has sent. Let T, be a variable A 0,o 0,- L for the number of messages i's computer B - L,O M, M sent (the number on i 's screen). Notice that sending the messages is not a state b strategic decision by the players. It is an probability p automatic device carried out by the comput- ers. The designer of the system sets up the co~municationnetwork between the players In the state of nature a(b) the players get and they can only choose between A and B a positive payoff, M, if both choose the after the communication phase has ended. action A(B). If they choose the same action If the two machnes exchange an infinite but it is the "wrong" one they get 0.If they number of messages, then we may say that fail to coordinate, then the player who played the two players have common knowledge B gets - L,where L > M. Thus, it is dan- that the game is G,. However, since only a gerous for a player to play B unless he is finite number of messages are transferred, confident enough that hs partner is going to the players never have common knowledge play B as well. The state a is the more likely that the game they play is G,. event: b appears with a priori probability of In choosing between A and B after the p <1/2. end of the communication phase, player 1 The information about the state of nature (and similarly player 2) faces uncertainty: is known initially only to player 1. Without given that he sent T, messages he does not transferring the information, the players know whether player 2 did not get the T,th message, or whether player 2 got the T,th message, but the T,th confirmation has been lost. Any number on the screen corresponds 'I should like to thank John Geanakopolos for refer- to a state of knowledge not only about the ring me to the "coordinated attack problem." state of nature but also about the other VOL.
Load more

Recommended publications
  • 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]
  • 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]
  • MATCHING with RENEGOTIATION 1. Introduction Deferred Acceptance
    MATCHING WITH RENEGOTIATION AKIHIKO MATSUI AND MEGUMI MURAKAMI Abstract. The present paper studies the deferred acceptance algorithm (DA) with renegotiation. After DA assigns objects to players, the players may renegotiate. The final allocation is prescribed by a renegotiation mapping, of which value is a strong core given an allocation induced by DA. We say that DA is strategy-proof with renegotiation if for any true preference profile and any (poten- tially false) report, an optimal strategy for each player is to submit the true preference. We then have the first theorem: DA is not strategy-proof with renegotiation for any priority structure. The priority structure is said to be unreversed if there are two players who have higher priority than the others at any object, and the other players are aligned in the same order across objects. Then, the second theorem states that the DA rule is implemented in Nash equilibrium with renegotiation, or equivalently, any Nash equilibrium of DA with renegotiation induces the same allocation as the DA rule, if and only if the priority structure is unreversed. Keywords: deferred acceptance algorithm (DA), indivisible object, renegotiation mapping, strong core, strategy-proofness with renegotiation, Nash implementation with renegotiation, unreversed priority JEL Classification Numbers: C78, D47 1. Introduction Deferred acceptance algorithm (DA) has been studied since the seminal paper by Gale and Shapley (1962). A class of problems investigated therein includes college admissions and office assignments. In these problems, the centralized mechanism assigns objects to players based on their preferences over objects and priorities for the objects over the players. Two notable prop- erties of DA are stability and strategy-proofness (Gale & Shapley, 1962; Dubins & Freedman, 1981; Roth, 1982).
    [Show full text]
  • Whither Game Theory? Towards a Theory of Learning in Games
    Whither Game Theory? Towards a Theory of Learning in Games The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Fudenberg, Drew, and David K. Levine. “Whither Game Theory? Towards a Theory of Learning in Games.” Journal of Economic Perspectives, vol. 30, no. 4, Nov. 2016, pp. 151–70. As Published http://dx.doi.org/10.1257/jep.30.4.151 Publisher American Economic Association Version Final published version Citable link http://hdl.handle.net/1721.1/113940 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Journal of Economic Perspectives—Volume 30, Number 4—Fall 2016—Pages 151–170 Whither Game Theory? Towards a Theory of Learning in Games Drew Fudenberg and David K. Levine hen we were graduate students at MIT (1977–81), the only game theory mentioned in the first-year core was static Cournot (1838) oligopoly, W although Eric Maskin taught an advanced elective on game theory and mechanism design. Just ten years later, game theory had invaded mainstream economic research and graduate education, and instructors had a choice of three graduate texts: Fudenberg and Tirole (1991), Osborne and Rubinstein (1994), and Myerson (1997). Game theory has been successful in economics because it works empirically in many important circumstances. Many of the theoretical applications in the 1980s involved issues in industrial organization, like commitment and timing in patent races and preemptive investment.
    [Show full text]
  • Economics 286: Game Theory 1 Overview
    Economics 286: Game Theory Stanford University, Fall 2016 Mon, Wed 9:30 – 11:20 AM, Landau 218 https://canvas.stanford.edu/courses/47170 Syllabus version: September 23, 2016 Gabriel Carroll, [email protected] | Landau 245 | Office hours by appointment 1 Overview What this class is: This is an intermediate-level, mathematically oriented class in game theory, aimed at economics PhD students (but qualified students in other depart- ments are very much welcome to attend). The goals are twofold: to provide technical tools for studying game-theoretic problems that arise in economic models, and to discuss conceptual issues in interpreting predictions made using game theory. What this class is not: • A class just for micro theorists. This class is meant to provide concepts and analytical tools useful in every area of economics (and beyond). • A first course in game theory. Technically, the mathematical content will be developed in a way that doesn’t presume game theory background; but in practice, if you haven’t taken a previous game theory class it will be steep going. (The official prerequisite is ECON 203. If you have taken a different game theory class and are unsure if you are prepared, you are encouraged to discuss with me.) • An introduction to the research frontiers. This is intended as a foundational course, although we will run across some relatively recent papers. ECON 290 or MGTECON 616 are more like “advanced topics” classes. Textbooks: The main source for this class, which covers much (though not all) of the material, is the still-classic • Drew Fudenberg and Jean Tirole, Game Theory, MIT Press, 1991.
    [Show full text]
  • Coalitional Rationalizability*
    Coalitional Rationalizability∗ Attila Ambrus This Version: September 2005 Abstract This paper investigates how groups or coalitions of players can act in their collective interest in non-cooperative normal form games even if equilibrium play is not assumed. The main idea is that each member of a coalition will confine play to a subset of their strategies if it is in their mutual interest to do so. An iterative procedure of restrictions is used to define a non-cooperative solution concept, the set of coalitionally rational- izable strategies. The procedure is analogous to iterative deletion of never best response strategies, but operates on implicit agreements by different coalitions. The solution set is a nonempty subset of the rationalizable strategies. ∗I thank Dilip Abreu for support and extremely valuable comments at all stages of writingthispaper.Iwouldalsoliketothank Drew Fudenberg, Faruk Gul, Wolfgang Pesendorfer, Ariel Rubinstein and Marciano Siniscalchi for useful comments and dis- cussions. Finally, I would like to thank Eddie Dekel, Haluk Ergin, Erica Field, Jozsef Molnar, Wojciech Oszlewski, Hugo Sonnenschein, Andrea Wilson, seminar participants at various universities for useful comments. 1 I. Introduction The main solution concept in noncooperative game theory, Nash equilibrium, requires stability only with respect to individual deviations by players. It does not take into account the possibility that groups of players might coordinate their moves, in order to achieve an outcome that is better for all of them. There have been several attempts to incorporate this consideration into the theory of noncooperative games, starting with the pioneering works of Schelling [1960] and Aumann [1959]. The latter offered strong Nash equilibrium, the first for- mal solution concept in noncooperative game theory that takes into account the interests of coalitions.
    [Show full text]
  • QUARTERLY JOURNAL of ECONOMICS Vol
    THE QUARTERLY JOURNAL OF ECONOMICS Vol. CXVII November 2002 Issue 4 NATURAL SELECTION AND THE ORIGIN OF ECONOMIC GROWTH* ODED GALOR AND OMER MOAV This research develops an evolutionary growth theory that captures the interplay between the evolution of mankind and economic growth since the emergence of the human species. The theory suggests that the struggle for survival that had characterized most of human existence generated an evolution- ary advantage to human traits that were complementary to the growth process, triggering the takeoff from an epoch of stagnation to sustained economic growth. “It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change” [Charles Darwin]. * We are grateful to Alberto Alesina, Edward Glaeser, and two referees for valuable comments. We benefited from discussions with Daron Acemoglu, Ken- neth Arrow, Abhijit Banerjee, Samuel Bowles, Partha Dasgupta, Eddie Dekel, Steven Durlauf, Martin Eichenbaum, Eric Gould, John Hassler, Elhanan Help- man, Peter Klenow, Michael Kremer, James Mirrlees, Joel Mokyr, Torsten Persson, Ariel Rubinstein, Nathan Sussman, David Weil, Fabrizio Zilibotti, con- ference participants in the European Economic Association meeting, Bolzano, August 2000; XIth European Economic Association Summer School, Barcelona, September 2000; Demography and Growth Conference, Harvard University, Sep- tember 2000; the MacArthur Meeting on Inequality and Economic Performance, Massachusetts Institute of Technology, October 2000; Winter Workshop of
    [Show full text]
  • Models in Microeconomic Theory Covers Basic Models in Current Microeconomic Theory
    4&5"+)$'0)#'785()&1$() !"#$%&'()'!(*+"$*")",(*'-.$"+/ Models in !0+1()'23'4&5"+)$'0)#'6+($%'785()&1$()' Microeconomic Theory Models in Microeconomic Theory covers basic models in current microeconomic theory. Part I (Chapters 1–7) presents models of an economic agent, discussing abstract models of preferences, choice, and decision making under uncertainty, before turning to models of the consumer, the producer, and monopoly. Part II (Chapters 8–14) introduces the concept of equilibrium, beginning, unconven� onally, with the models of the jungle and an economy with indivisible goods, and con� nuing with models of an exchange economy, equilibrium with ra� onal expecta� ons, and an economy with asymmetric informa� on. Part III (Chapters Martin J. Osborne 15–16) provides an introduc� on to game theory, covering strategic and extensive games and the concepts of Nash equilibrium and subgame perfect equilibrium. Part IV (Chapters '''''''''''!"#$%&'()'!(*+"$*")",(*'-.$"+/'''' Ariel Rubinstein 17–20) gives a taste of the topics of mechanism design, matching, the axioma� c analysis of economic systems, and social choice. The book focuses on the concepts of model and equilibrium. It states models and results precisely, and provides proofs for all results. It uses only elementary mathema� cs (with almost no calculus), although many of the proofs involve sustained logical arguments. It includes about 150 exercises. With its formal but accessible style, this textbook is designed for undergraduate students of microeconomics at intermediate and advanced levels. As with all Open Book publica� ons, this en� re book is available to read for free on the publisher’s website. Printed and digital edi� ons, together with supplementary digital material, can also be found at www.openbookpublishers.com Cover design by Mar� n J.
    [Show full text]
  • Games with Switching Costs and Endogenous References*
    Games with Switching Costs and Endogenous References* Begum Guney† Michael Richter‡ June 30, 2021 Abstract We introduce a game-theoretic model with switching costs and endogenous references. An agent endogenizes his reference strategy and then, taking switching costs into account, he selects a strategy from which there is no profitable deviation. We axiomatically characterize this selection procedure in one-player games. We then extend this procedure to multi-player simultaneous games by defining a Switching Cost Nash Equilibrium (SNE) notion, and prove that (i) an SNE always exists; (ii) there are sets of SNE which can never be a set of Nash Equilibrium for any standard game; and (iii) SNE with a specific cost structure exactly characterizes the Nash Equilibrium of nearby games, in contrast to Rad- ner’s (1980) "-equilibrium. Subsequently, we apply our SNE notion to a product differentiation model, and reach the opposite conclusion of Radner (1980): switching costs for firms may benefit consumers. Finally, we compare our model with others, especially Koszegi¨ and Rabin’s (2006) personal equilibrium. Keywords: Switching Cost Nash Equilibrium, Choice, Endogenous Reference, Switching Costs, Epsilon Equilibrium JEL classification: D00, D01, D03, C72 *We thank Levent Koc¸kesen, Yusufcan Masatlioglu, George Mailath, Ariel Rubinstein, Rani Spiegler, Roee Teper, and three anonymous referees for their helpful comments and suggestions. The first author acknowledges financial support from the Scientific and Technological Research Council of Turkey, Project #113K370. †Department of Economics, Ozyegin University. E-mail: [email protected] ‡Department of Economics, Royal Holloway, University of London. E-mail: [email protected] 1 1 Introduction Switching costs are a feature of daily life.
    [Show full text]
  • Monetary Policy, Bounded Rationality, and Incomplete Markets∗
    Monetary Policy, Bounded Rationality, and Incomplete Markets∗ Emmanuel Farhi Iván Werning Harvard University MIT January 2019 This paper extends the benchmark New-Keynesian model by introducing two frictions: (1) agent heterogeneity with incomplete markets, uninsurable idiosyncratic risk, and occasionally- binding borrowing constraints; and (2) bounded rationality in the form of level-k thinking. Compared to the benchmark model, we show that the interaction of these two frictions leads to a powerful mitigation of the effects of monetary policy, which is more pronounced at long horizons, and offers a potential rationalization of the “forward guidance puzzle”. Each of these frictions, in isolation, would lead to no or much smaller departures from the benchmark model. 1 Introduction The baseline New Keynesian setup is a workhorse model for monetary policy analysis. How- ever, in its basic form, it also has implications that are controversial or unrealistic. For example, despite various concrete results that limit the number of equilibria, indeterminacy concerns re- main. In addition, although the model provides a rationale for effective monetary policy, some view the power of monetary policy as too effective, and changes in future interest rates may be especially powerful—the so-called “forward guidance puzzle”.1 Finally, while the model can ∗Farhi: [email protected]; Department of Economics, Harvard University, 1805 Cambridge Street, 02138, Cambridge, MA, USA. Werning: [email protected]; Department of Economics, MIT, 50 Memorial Drive, 02139, Cambridge, MA, USA. We are grateful to Mikel Petri, who provided outstanding research assistance. For use- ful comments we thank Xavier Gabaix, Jordi Gali, Mark Gertler, Luigi Iovino, Benoit Mojon, Martin Schneider, Andrei Shleifer, Gianluca Violante, Mirko Wiederholt, and Michael Woodford.
    [Show full text]
  • Game Theory: Syllabus
    Game Theory: Syllabus Instructor: Xiang Sun Wuhan University, Economics and Management School Academic Year 2015–2016, Semester 1 Chinese title: 博弈论 Prerequisite: Calculus, Probability, Advanced Microeconomics, Basic Game Theory Course description: This module introduces students in economics and other social sciences to game theory, a theory of interactive decision making. The module focuses on presenting basic concepts, core ideas, main results, and recent developments. Modular credit: 3 modular credits Modular number: Time: Week 1–9, Tuesday and Wednesday, 14:05–14:50, 14:55–15:40, 15:45–16:30 Venue: 枫-314 Module website: http://www.xiangsun.org/teaching. Instructor: 孙祥 • E-mail: [email protected] • Homepage: http://www.xiangsun.org. If you can not access, please use VPN. • Office: Room A501-2, Liangsheng Building • Telephone: +86 027 6875 5072 • Mailbox: 11-13 Office hours: By appointment Teaching assistants: 瞿爱霞、杨胜寒 1 Game Theory 2/4 Syllabus Main references: [OR] Martin J. Osborne and Ariel Rubinstein, A Course in Game Theory, MIT Press, 1994. Electronic version is available at Osborne’s homepage or Rubinstein’s homepage. The latest version is on 24 Sep. 2012. [Sun] Xiang Sun, Lecture Notes on Game Theory: Theory and Examples, 2015. Electronic version is available at Sun’s homepage. Language: Lecture notes Lectures Homework sets Mid-term test Final examination Chinese X English X X X X X Supplementary readings: * Robert J. Aumann, Lectures on Game Theory, Westview Press, 1989. * Drew Fudenberg and Jean Tirole, Game Theory, MIT Press, 1991. * Robert Gibbons, Game Theory for Applied Economists, Princeton University Press, 1992. • Matthew O.
    [Show full text]
  • Book Review:" a Beautiful Math. John Nash, Game Theory, and the Modern
    Book Review: “A Beautiful Math. John Nash, Game Theory, and the Modern Quest for a Code of Nature” by Tom Siegfried Joseph Henry Press (2006) Paul B. Slater∗ ISBER, University of California, Santa Barbara, 93106. In the collection of modeling paradigms available to scientific researchers, none has proved perhaps as productive and insightful as the game-theoretic one–in the development of which, the eminent mathematician John Forbes Nash played a most pivotal role (having introduced the concept of non-cooperative games [MR0043432, MR0031701, MR0035977], complementing the landmark [zero-sum, minimax] work of Von Neumann and Morgenstern [MR0011937 and MR2316805]). This is the interestingly and certainly well-defended and documented–although not universally accepted–position taken by Tom Siegfried in his concise book, ”The Beautiful Mind: John Nash, Game Theory, and the Modern Quest for a Code of Nature”. (The dis- tinguished economist and game-theorist Ariel Rubinstein is a notable nay-sayer–”the challenges facing the world today are far too complex to be captured by any matrix game” (p. 68). Further, the Nash equilibrium is a static concept, and the dynamics required to achieve it are problem- atical, with pay-offs being assumed to depend continuously on the various decisions taken [I. Ekeland, ”Game theory: Agreeing on strategies”, Nature 400, 623-624 (12 August 1999)]. While Siegfried’s book is essentially concerned with the application of equilibrium concepts, the author does note (p. 238) a reviewer’s comments that, in some cases, a more appropriate description arXiv:0901.4054v1 [math.HO] 26 Jan 2009 might be provided by a chaotic system [cf.
    [Show full text]