Ex-Post Stability in Large Games (Draft, Comments Welcome)
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Minimax TD-Learning with Neural Nets in a Markov Game
Minimax TD-Learning with Neural Nets in a Markov Game Fredrik A. Dahl and Ole Martin Halck Norwegian Defence Research Establishment (FFI) P.O. Box 25, NO-2027 Kjeller, Norway {Fredrik-A.Dahl, Ole-Martin.Halck}@ffi.no Abstract. A minimax version of temporal difference learning (minimax TD- learning) is given, similar to minimax Q-learning. The algorithm is used to train a neural net to play Campaign, a two-player zero-sum game with imperfect information of the Markov game class. Two different evaluation criteria for evaluating game-playing agents are used, and their relation to game theory is shown. Also practical aspects of linear programming and fictitious play used for solving matrix games are discussed. 1 Introduction An important challenge to artificial intelligence (AI) in general, and machine learning in particular, is the development of agents that handle uncertainty in a rational way. This is particularly true when the uncertainty is connected with the behavior of other agents. Game theory is the branch of mathematics that deals with these problems, and indeed games have always been an important arena for testing and developing AI. However, almost all of this effort has gone into deterministic games like chess, go, othello and checkers. Although these are complex problem domains, uncertainty is not their major challenge. With the successful application of temporal difference learning, as defined by Sutton [1], to the dice game of backgammon by Tesauro [2], random games were included as a standard testing ground. But even backgammon features perfect information, which implies that both players always have the same information about the state of the game. -
California Institute of Technology
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Caltech Authors - Main DIVISION OF THE HUM ANITIES AND SO CI AL SCIENCES CALIFORNIA INSTITUTE OF TECHNOLOGY PASADENA, CALIFORNIA 91125 IMPLEMENTATION THEORY Thomas R. Palfrey � < a: 0 1891 u. "')/,.. () SOCIAL SCIENCE WORKING PAPER 912 September 1995 Implementation Theory Thomas R. Palfrey Abstract This surveys the branch of implementation theory initiated by Maskin (1977). Results for both complete and incomplete information environments are covered. JEL classification numbers: 025, 026 Key words: Implementation Theory, Mechanism Design, Game Theory, Social Choice Implementation Theory* Thomas R. Palfrey 1 Introduction Implementation theory is an area of research in economic theory that rigorously investi gates the correspondence between normative goals and institutions designed to achieve {implement) those goals. More precisely, given a normative goal or welfare criterion for a particular class of allocation pro blems (or domain of environments) it formally char acterizes organizational mechanisms that will guarantee outcomes consistent with that goal, assuming the outcomes of any such mechanism arise from some specification of equilibrium behavior. The approaches to this problem to date lie in the general domain of game theory because, as a matter of definition in the implementation theory litera ture, an institution is modelled as a mechanism, which is essentially a non-cooperative game. Moreover, the specific models of equilibrium behavior -
Can Game Theory Be Used to Address PPP Renegotiations?
Can game theory be used to address PPP renegotiations? A retrospective study of the of the Metronet - London Underground PPP By Gregory Michael Kennedy [152111301] Supervisors Professor Ricardo Ferreira Reis, PhD Professor Joaquim Miranda Sarmento, PhD Dissertation submitted in partial fulfilment of requirements for the degree of MSc in Business Administration, at the Universidade Católica Portuguesa June 2013 Abstract of thesis entitled “Can game theory be used to address PPP renegotiations? A retrospective study of the of the Metronet - London Underground PPP” Submitted by Gregory Michael Kennedy (152111301) In partial fulfilment of requirements for the degree of MSc in Business Administration, at the Universidade Católica Portuguesa June 2013 Public Private Partnerships (PPPs) have been introduced in many countries in order to increase the supply of public infrastructure services. The main criterion for implementing a PPP is that it will provide value for money. Often, however, these projects enter into financial distress which requires that they either be rescued or retendered. The cost of such a financial renegotiation can erode the value for money supposed to be created by the PPP. Due to the scale and complexity of these projects, the decision either to rescue or retender the project is not straightforward. We determine whether game theory can aid the decision making process in PPP renegotiation by applying a game theory model retrospectively to the failure of the Metronet - London Underground PPP. We study whether the model can be applied to a real PPP case, whether the application of this model would have changed the outcome of the case and, finally, whether and how the model can be used in future PPP renegotiations. -
Viable Nash Equilibria: Formation and Defection (Feb 2020)
VIABLE NASH EQUILIBRIA: FORMATION AND DEFECTION (FEB 2020) EHUD KALAI In memory of John Nash Abstract. To be credible, economic analysis should restrict itself to the use of only those Nash equilibria that are viable. To assess the viability of an equilibrium , I study simple dual indices: a formation index, F (), that speci…es the number of loyalists needed to form ; and a defection index, D(), that speci…es the number of defectors that can sustain. Surprisingly, these simple indices (1) predict the performance of Nash equilibria in social systems and lab experiments, and (2) uncover new prop- erties of Nash equilibria and stability issues that have so far eluded game theory re…nements. JEL Classi…cation Codes: C0, C7, D5, D9. 1. Overview Current economic analysis often relies on the notion of a Nash equilibrium. Yet there are mixed opinions about the viability of this notion. On the one hand, many equilibria, referred to as viable in this paper, play critical roles in functioning social systems and perform well in lab and …eld experiments. Date: March 9, 2018, this version Feb 24, 2020. Key words and phrases. Normal form games, Nash equilibrium, Stability, Fault tolerance, Behavioral Economics. The author thanks the following people for helpful conversations: Nemanja Antic, Sunil Chopra, Vince Crawford, K…r Eliaz, Drew Fudenberg, Ronen Gradwohl, Yingni Guo, Adam Kalai, Fern Kalai, Martin Lariviere, Eric Maskin, Rosemarie Nagel, Andy Postlewaite, Larry Samuelson, David Schmeidler, James Schummer, Eran Shmaya, Joel Sobel, and Peyton Young; and seminar participants at the universities of the Basque Country, Oxford, Tel Aviv, Yale, Stanford, Berkeley, Stony Brook, Bar Ilan, the Technion, and the Hebrew University. -
Bounded Rationality and Correlated Equilibria Fabrizio Germano, Peio Zuazo-Garin
Bounded Rationality and Correlated Equilibria Fabrizio Germano, Peio Zuazo-Garin To cite this version: Fabrizio Germano, Peio Zuazo-Garin. Bounded Rationality and Correlated Equilibria. 2015. halshs- 01251512 HAL Id: halshs-01251512 https://halshs.archives-ouvertes.fr/halshs-01251512 Preprint submitted on 6 Jan 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Working Papers / Documents de travail Bounded Rationality and Correlated Equilibria Fabrizio Germano Peio Zuazo-Garin WP 2015 - Nr 51 Bounded Rationality and Correlated Equilibria∗ Fabrizio Germano† and Peio Zuazo-Garin‡ November 2, 2015 Abstract We study an interactive framework that explicitly allows for nonrational behavior. We do not place any restrictions on how players’ behavior deviates from rationality. Instead we assume that there exists a probability p such that all players play rationally with at least probability p, and all players believe, with at least probability p, that their opponents play rationally. This, together with the assumption of a common prior, leads to what we call the set of p-rational outcomes, which we define and characterize for arbitrary probability p. We then show that this set varies continuously in p and converges to the set of correlated equilibria as p approaches 1, thus establishing robustness of the correlated equilibrium concept to relaxing rationality and common knowledge of rationality. -
DP Cover1512 Kalai.Cdr
Discussion Paper #1512 June 16, 2010 A A Cooperative Value for Bayesian Games Key words: cooperative game theory, non- cooperative game theory, bargaining, min-max value JEL classification: C70, C71, C72, C78 Adam Kalai Microsoft Research Ehud Kalai Northwestern University www.kellogg.northwestern.edu/research/math everone Hall Evanston, IL 60208-2014 US CMS-EMS oad 580 L The Center for Mathematical Studies in Economics & Management Sciences Northwestern University 2001 Sheridan R A COOPERATIVE VALUE FOR BAYESIAN GAMES ADAM TAUMAN KALAI∗ AND EHUD KALAIy;x Abstract. Selfish, strategic players may benefit from cooperation, provided they reach agreement. It is therefore important to construct mechanisms that facilitate such cooperation, especially in the case of asymmetric private information. The two major issues are: (1) singling out a fair and efficient outcome among the many individually rational possibilities in a strategic game, and (2) establishing a play protocol under which strategic players may achieve this outcome. The paper presents a general solution for two-person Bayesian games with monetary payoffs, under a strong revealed-payoff assumption. The proposed solution builds upon earlier concepts in game theory. It coincides with the von Neumann minmax value on the class of zero sum games and with the major solution concepts to the Nash Bargaining Problem. Moreover, the solution is based on a simple decomposition of every game into cooperative and competitive components, which is easy to compute. 1. Introduction Selfish players in strategic games benefit from cooperation, provided they come to mutually beneficial agreements. In the case of asymmetric private information, the benefits may be even greater, but avoiding strategic manipulations is more subtle. -
Game Theory with Translucent Players
Game Theory with Translucent Players Joseph Y. Halpern and Rafael Pass∗ Cornell University Department of Computer Science Ithaca, NY, 14853, U.S.A. e-mail: fhalpern,[email protected] November 27, 2012 Abstract A traditional assumption in game theory is that players are opaque to one another—if a player changes strategies, then this change in strategies does not affect the choice of other players’ strategies. In many situations this is an unrealistic assumption. We develop a framework for reasoning about games where the players may be translucent to one another; in particular, a player may believe that if she were to change strategies, then the other player would also change strategies. Translucent players may achieve significantly more efficient outcomes than opaque ones. Our main result is a characterization of strategies consistent with appro- priate analogues of common belief of rationality. Common Counterfactual Belief of Rationality (CCBR) holds if (1) everyone is rational, (2) everyone counterfactually believes that everyone else is rational (i.e., all players i be- lieve that everyone else would still be rational even if i were to switch strate- gies), (3) everyone counterfactually believes that everyone else is rational, and counterfactually believes that everyone else is rational, and so on. CCBR characterizes the set of strategies surviving iterated removal of minimax dom- inated strategies: a strategy σi is minimax dominated for i if there exists a 0 0 0 strategy σ for i such that min 0 u (σ ; µ ) > max u (σ ; µ ). i µ−i i i −i µ−i i i −i ∗Halpern is supported in part by NSF grants IIS-0812045, IIS-0911036, and CCF-1214844, by AFOSR grant FA9550-08-1-0266, and by ARO grant W911NF-09-1-0281. -
Matthew O. Jackson
Matthew O. Jackson Department of Economics Stanford University Stanford, CA 94305-6072 (650) 723-3544, fax: 725-5702, [email protected] http://www.stanford.edu/ jacksonm/ ⇠ Personal: Born 1962. Married to Sara Jackson. Daughters: Emilie and Lisa. Education: Ph.D. in Economics from the Graduate School of Business, Stanford Uni- versity, 1988. Bachelor of Arts in Economics, Summa Cum Laude, Phi Beta Kappa, Princeton University, 1984. Full-Time Appointments: 2008-present, William D. Eberle Professor of Economics, Stanford Univer- sity. 2006-2008, Professor of Economics, Stanford University. 2002-2006, Edie and Lew Wasserman Professor of Economics, California Institute of Technology. 1997-2002, Professor of Economics, California Institute of Technology. 1996-1997, IBM Distinguished Professor of Regulatory and Competitive Practices MEDS department (Managerial Economics and Decision Sci- ences), Kellogg Graduate School of Management, Northwestern Univer- sity. 1995-1996, Mechthild E. Nemmers Distinguished Professor MEDS, Kellogg Graduate School of Management, Northwestern University. 1993-1994 , Professor (MEDS), Kellogg Graduate School of Management, Northwestern University. 1991-1993, Associate Professor (MEDS), Kellogg Graduate School of Man- agement, Northwestern University. 1988-1991, Assistant Professor, (MEDS), Kellogg Graduate School of Man- agement, Northwestern University. Honors : Jean-Jacques La↵ont Prize, Toulouse School of Economics 2020. President, Game Theory Society, 2020-2022, Exec VP 2018-2020. Game Theory Society Fellow, elected 2017. John von Neumann Award, Rajk L´aszl´oCollege, 2015. Member of the National Academy of Sciences, elected 2015. Honorary Doctorate (Doctorat Honoris Causa), Aix-Marseille Universit´e, 2013. Dean’s Award for Distinguished Teaching in Humanities and Sciences, Stanford, 2013. Distinguished Teaching Award: Stanford Department of Economics, 2012. -
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© October 2017 | IJIRT | Volume 4 Issue 5 | ISSN: 2349-6002 The Analogous Application of Game Theory and Monte Carlo Simulation Techniques from World War II to Business Decision Making Dhriti Malviya1, Disha Gupta2, Hiya Banerjee3, Dhairya Shah4, Eashan Shetty5 1, 2,3,4,5 Narsee Monjee Institute of Management Studies, Mumbai, India Abstract- The Second World War, one of the most ‗Operations Research‘ only came up in the year 1940. gruelling events in the history of mankind, also marks During World War II, a team of humans referred to the emergence of one of modern-day’s most widely used as the Blackett‘s Circus in UK first applied scientific scientific disciplines – Operations Research (OR). techniques to analyze military operations to win the Rather than defining OR as a ‘part of mathematics’, a war and thus developed the scientific discipline – better characterization of the sequence of events would be that some mathematicians during World War II Operations Research. Operations Research includes were coerced into mixed disciplinary units dominated plenty of problem-solving techniques like by physicists and statisticians, and directed to mathematical models, statistics and algorithms to participate in an assorted mix of activities which were assist in decision-making. OR is used to analyze clubbed together under the rubric of ‘Operations advanced real-world systems, typically with the Research’. Some of these activities ranged from target of improving or optimizing the tasks. curating a solution for the neutron scattering problem The aim during WWII was to get utmost economical in atomic bomb design to strategizing military attacks usage of restricted military resources by the by means of choosing the best possible route to travel. -
Large Games: Structural Robustness
1 Large games: structural robustness Ehud Kalai Northwestern University Forthcoming in The New Palgrave Dictionary of Economics , 2 nd edition, Palgrave Macmillan ABSTRACT In simultaneous-move Bayesian games with many semi-anonymous players all the equilibria are structurally robust. The equilibria survive under structural alterations of the rules of the game and its information structure, even when the game is embedded in bigger games. Structural robustness implies ex-post Nash condition s and a stronger condition of information proofness. It also implies fast learning, self-purification and strong rational expectations in market games. Structurally robust equilibria may be used to model games with highly unspecified structures, such as games played on the web. 0. Background on large games Earlier literature on large (many players) cooperative games is surveyed in Aumann and Shapley (1974). For large strategic games, see Schmeidler (1973) and the follow-up literature on the purification of Nash equilibria. There is also substantial literature on large games with special structures, for example large auctions as reported in Rustichini, Satterthwaite, and Williams (1994). Unlike the above, this survey concentrates on the structural robustness of (general) Bayesian games with many semi-anonymous players, as developed in Kalai (2004, 2005). (For additional notions of robustness in game theory, see Bergemann and Morris, 2005). 1. Main message and examples In simultaneous-move Bayesian games with many semi-anonymous players, all Nash equilibria are structurally robust. The equilibria survive under structural alterations that 2 relax the simultaneous-play assumptions, and permit information transmission, revisions of choices, communication, commitments, delegation, and more. Large economic and political systems and distributive systems such as the Web are examples of environments that give rise to such games. -
Bayesian Games Professors Greenwald 2018-01-31
Bayesian Games Professors Greenwald 2018-01-31 We describe incomplete-information, or Bayesian, normal-form games (formally; no examples), and corresponding equilibrium concepts. 1 A Bayesian Model of Interaction A Bayesian, or incomplete information, game is a generalization of a complete-information game. Recall that in a complete-information game, the game is assumed to be common knowledge. In a Bayesian game, in addition to what is common knowledge, players may have private information. This private information is captured by the notion of an epistemic type, which describes a player’s knowledge. The Bayesian-game formalism makes two simplifying assumptions: • Any information that is privy to any of the players pertains only to utilities. In all realizations of a Bayesian game, the number of players and their actions are identical. • Players maintain beliefs about the game (i.e., about utilities) in the form of a probability distribution over types. Prior to receiving any private information, this probability distribution is common knowledge: i.e., it is a common prior. After receiving private information, players conditional on this information to update their beliefs. As a consequence of the com- mon prior assumption, any differences in beliefs can be attributed entirely to differences in information. Rational players are again assumed to maximize their utility. But further, they are assumed to update their beliefs when they obtain new information via Bayes’ rule. Thus, in a Bayesian game, in addition to players, actions, and utilities, there is a type space T = ∏i2[n] Ti, where Ti is the type space of player i.There is also a common prior F, which is a probability distribution over type profiles. -
Gibbard Satterthwaite Theorem and Arrow Impossibility
Game Theory Lecture Notes By Y. Narahari Department of Computer Science and Automation Indian Institute of Science Bangalore, India July 2012 The Gibbard Satterthwaite Theorem and Arrow’s Impossibility Theorem Note: This is a only a draft version, so there could be flaws. If you find any errors, please do send email to [email protected]. A more thorough version would be available soon in this space. 1 The Gibbard–Satterthwaite Impossibility Theorem We have seen in the last section that dominant strategy incentive compatibility is an extremely de- sirable property of social choice functions. However the DSIC property, being a strong one, precludes certain other desirable properties to be satisfied. In this section, we discuss the Gibbard–Satterthwaite impossibility theorem (G–S theorem, for short), which shows that the DSIC property will force an SCF to be dictatorial if the utility environment is an unrestricted one. In fact, in the process, even ex-post efficiency will have to be sacrificed. One can say that the G–S theorem has shaped the course of research in mechanism design during the 1970s and beyond, and is therefore a landmark result in mechanism design theory. The G–S theorem is credited independently to Gibbard in 1973 [1] and Satterthwaite in 1975 [2]. The G–S theorem is a brilliant reinterpretation of the famous Arrow’s im- possibility theorem (which we discuss in the next section). We start our discussion of the G–S theorem with a motivating example. Example 1 (Supplier Selection Problem) We have seen this example earlier (Example 2.29).