Ten Little Treasures of Game Theory and Ten Intuitive Contradictions
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Equilibrium Refinements
Equilibrium Refinements Mihai Manea MIT Sequential Equilibrium I In many games information is imperfect and the only subgame is the original game. subgame perfect equilibrium = Nash equilibrium I Play starting at an information set can be analyzed as a separate subgame if we specify players’ beliefs about at which node they are. I Based on the beliefs, we can test whether continuation strategies form a Nash equilibrium. I Sequential equilibrium (Kreps and Wilson 1982): way to derive plausible beliefs at every information set. Mihai Manea (MIT) Equilibrium Refinements April 13, 2016 2 / 38 An Example with Incomplete Information Spence’s (1973) job market signaling game I The worker knows her ability (productivity) and chooses a level of education. I Education is more costly for low ability types. I Firm observes the worker’s education, but not her ability. I The firm decides what wage to offer her. In the spirit of subgame perfection, the optimal wage should depend on the firm’s beliefs about the worker’s ability given the observed education. An equilibrium needs to specify contingent actions and beliefs. Beliefs should follow Bayes’ rule on the equilibrium path. What about off-path beliefs? Mihai Manea (MIT) Equilibrium Refinements April 13, 2016 3 / 38 An Example with Imperfect Information Courtesy of The MIT Press. Used with permission. Figure: (L; A) is a subgame perfect equilibrium. Is it plausible that 2 plays A? Mihai Manea (MIT) Equilibrium Refinements April 13, 2016 4 / 38 Assessments and Sequential Rationality Focus on extensive-form games of perfect recall with finitely many nodes. An assessment is a pair (σ; µ) I σ: (behavior) strategy profile I µ = (µ(h) 2 ∆(h))h2H: system of beliefs ui(σjh; µ(h)): i’s payoff when play begins at a node in h randomly selected according to µ(h), and subsequent play specified by σ. -
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. -
Recent Advances in Understanding Competitive Markets
Recent Advances in Understanding Competitive Markets Chris Shannon Department of Economics University of California, Berkeley March 4, 2002 1 Introduction The Arrow-Debreu model of competitive markets has proven to be a remark- ably rich and °exible foundation for studying an array of important economic problems, ranging from social security reform to the determinants of long-run growth. Central to the study of such questions are many of the extensions and modi¯cations of the classic Arrow-Debreu framework that have been ad- vanced over the last 40 years. These include dynamic models of exchange over time, as in overlapping generations or continuous time, and under un- certainty, as in incomplete ¯nancial markets. Many of the most interesting and important recent advances have been spurred by questions about the role of markets in allocating resources and providing opportunities for risk- sharing arising in ¯nance and macroeconomics. This article is intended to give an overview of some of these more recent developments in theoretical work involving competitive markets, and highlight some promising areas for future work. I focus on three broad topics. The ¯rst is the role of asymmetric informa- tion in competitive markets. Classic work in information economics suggests that competitive markets break down in the face of informational asymme- 0 tries. Recently these issues have been reinvestigated from the vantage point of more general models of the market structure, resulting in some surpris- ing results overturning these conclusions and clarifying the conditions under which perfectly competitive markets can incorporate informational asymme- tries. The second concentrates on the testable implications of competitive markets. -
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. -
Stochastic Game Theory Applications for Power Management in Cognitive Networks
STOCHASTIC GAME THEORY APPLICATIONS FOR POWER MANAGEMENT IN COGNITIVE NETWORKS A thesis submitted to Kent State University in partial fulfillment of the requirements for the degree of Master of Digital Science by Sham Fung Feb 2014 Thesis written by Sham Fung M.D.S, Kent State University, 2014 Approved by Advisor , Director, School of Digital Science ii TABLE OF CONTENTS LIST OF FIGURES . vi LIST OF TABLES . vii Acknowledgments . viii Dedication . ix 1 BACKGROUND OF COGNITIVE NETWORK . 1 1.1 Motivation and Requirements . 1 1.2 Definition of Cognitive Networks . 2 1.3 Key Elements of Cognitive Networks . 3 1.3.1 Learning and Reasoning . 3 1.3.2 Cognitive Network as a Multi-agent System . 4 2 POWER ALLOCATION IN COGNITIVE NETWORKS . 5 2.1 Overview . 5 2.2 Two Communication Paradigms . 6 2.3 Power Allocation Scheme . 8 2.3.1 Interference Constraints for Primary Users . 8 2.3.2 QoS Constraints for Secondary Users . 9 2.4 Related Works on Power Management in Cognitive Networks . 10 iii 3 GAME THEORY|PRELIMINARIES AND RELATED WORKS . 12 3.1 Non-cooperative Game . 14 3.1.1 Nash Equilibrium . 14 3.1.2 Other Equilibriums . 16 3.2 Cooperative Game . 16 3.2.1 Bargaining Game . 17 3.2.2 Coalition Game . 17 3.2.3 Solution Concept . 18 3.3 Stochastic Game . 19 3.4 Other Types of Games . 20 4 GAME THEORETICAL APPROACH ON POWER ALLOCATION . 23 4.1 Two Fundamental Types of Utility Functions . 23 4.1.1 QoS-Based Game . 23 4.1.2 Linear Pricing Game . -
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. -
Deterministic and Stochastic Prisoner's Dilemma Games: Experiments in Interdependent Security
NBER TECHNICAL WORKING PAPER SERIES DETERMINISTIC AND STOCHASTIC PRISONER'S DILEMMA GAMES: EXPERIMENTS IN INTERDEPENDENT SECURITY Howard Kunreuther Gabriel Silvasi Eric T. Bradlow Dylan Small Technical Working Paper 341 http://www.nber.org/papers/t0341 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 August 2007 We appreciate helpful discussions in designing the experiments and comments on earlier drafts of this paper by Colin Camerer, Vince Crawford, Rachel Croson, Robyn Dawes, Aureo DePaula, Geoff Heal, Charles Holt, David Krantz, Jack Ochs, Al Roth and Christian Schade. We also benefited from helpful comments from participants at the Workshop on Interdependent Security at the University of Pennsylvania (May 31-June 1 2006) and at the Workshop on Innovation and Coordination at Humboldt University (December 18-20, 2006). We thank George Abraham and Usmann Hassan for their help in organizing the data from the experiments. Support from NSF Grant CMS-0527598 and the Wharton Risk Management and Decision Processes Center is gratefully acknowledged. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. © 2007 by Howard Kunreuther, Gabriel Silvasi, Eric T. Bradlow, and Dylan Small. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Deterministic and Stochastic Prisoner's Dilemma Games: Experiments in Interdependent Security Howard Kunreuther, Gabriel Silvasi, Eric T. Bradlow, and Dylan Small NBER Technical Working Paper No. 341 August 2007 JEL No. C11,C12,C22,C23,C73,C91 ABSTRACT This paper examines experiments on interdependent security prisoner's dilemma games with repeated play. -
Stochastic Games with Hidden States∗
Stochastic Games with Hidden States¤ Yuichi Yamamoto† First Draft: March 29, 2014 This Version: January 14, 2015 Abstract This paper studies infinite-horizon stochastic games in which players ob- serve noisy public information about a hidden state each period. We find that if the game is connected, the limit feasible payoff set exists and is invariant to the initial prior about the state. Building on this invariance result, we pro- vide a recursive characterization of the equilibrium payoff set and establish the folk theorem. We also show that connectedness can be replaced with an even weaker condition, called asymptotic connectedness. Asymptotic con- nectedness is satisfied for generic signal distributions, if the state evolution is irreducible. Journal of Economic Literature Classification Numbers: C72, C73. Keywords: stochastic game, hidden state, connectedness, stochastic self- generation, folk theorem. ¤The author thanks Naoki Aizawa, Drew Fudenberg, Johannes Horner,¨ Atsushi Iwasaki, Michi- hiro Kandori, George Mailath, Takeaki Sunada, and Masatoshi Tsumagari for helpful conversa- tions, and seminar participants at various places. †Department of Economics, University of Pennsylvania. Email: [email protected] 1 1 Introduction When agents have a long-run relationship, underlying economic conditions may change over time. A leading example is a repeated Bertrand competition with stochastic demand shocks. Rotemberg and Saloner (1986) explore optimal col- lusive pricing when random demand shocks are i.i.d. each period. Haltiwanger and Harrington (1991), Kandori (1991), and Bagwell and Staiger (1997) further extend the analysis to the case in which demand fluctuations are cyclic or persis- tent. One of the crucial assumptions of these papers is that demand shocks are publicly observable before firms make their decisions in each period. -
A Beautiful Math : John Nash, Game Theory, and the Modern Quest for a Code of Nature / Tom Siegfried
A BEAUTIFULA BEAUTIFUL MATH MATH JOHN NASH, GAME THEORY, AND THE MODERN QUEST FOR A CODE OF NATURE TOM SIEGFRIED JOSEPH HENRY PRESS Washington, D.C. Joseph Henry Press • 500 Fifth Street, NW • Washington, DC 20001 The Joseph Henry Press, an imprint of the National Academies Press, was created with the goal of making books on science, technology, and health more widely available to professionals and the public. Joseph Henry was one of the founders of the National Academy of Sciences and a leader in early Ameri- can science. Any opinions, findings, conclusions, or recommendations expressed in this volume are those of the author and do not necessarily reflect the views of the National Academy of Sciences or its affiliated institutions. Library of Congress Cataloging-in-Publication Data Siegfried, Tom, 1950- A beautiful math : John Nash, game theory, and the modern quest for a code of nature / Tom Siegfried. — 1st ed. p. cm. Includes bibliographical references and index. ISBN 0-309-10192-1 (hardback) — ISBN 0-309-65928-0 (pdfs) 1. Game theory. I. Title. QA269.S574 2006 519.3—dc22 2006012394 Copyright 2006 by Tom Siegfried. All rights reserved. Printed in the United States of America. Preface Shortly after 9/11, a Russian scientist named Dmitri Gusev pro- posed an explanation for the origin of the name Al Qaeda. He suggested that the terrorist organization took its name from Isaac Asimov’s famous 1950s science fiction novels known as the Foun- dation Trilogy. After all, he reasoned, the Arabic word “qaeda” means something like “base” or “foundation.” And the first novel in Asimov’s trilogy, Foundation, apparently was titled “al-Qaida” in an Arabic translation. -
570: Minimax Sample Complexity for Turn-Based Stochastic Game
Minimax Sample Complexity for Turn-based Stochastic Game Qiwen Cui1 Lin F. Yang2 1School of Mathematical Sciences, Peking University 2Electrical and Computer Engineering Department, University of California, Los Angeles Abstract guarantees are rather rare due to complex interaction be- tween agents that makes the problem considerably harder than single agent reinforcement learning. This is also known The empirical success of multi-agent reinforce- as non-stationarity in MARL, which means when multi- ment learning is encouraging, while few theoret- ple agents alter their strategies based on samples collected ical guarantees have been revealed. In this work, from previous strategy, the system becomes non-stationary we prove that the plug-in solver approach, proba- for each agent and the improvement can not be guaranteed. bly the most natural reinforcement learning algo- One fundamental question in MBRL is that how to design rithm, achieves minimax sample complexity for efficient algorithms to overcome non-stationarity. turn-based stochastic game (TBSG). Specifically, we perform planning in an empirical TBSG by Two-players turn-based stochastic game (TBSG) is a two- utilizing a ‘simulator’ that allows sampling from agents generalization of Markov decision process (MDP), arbitrary state-action pair. We show that the em- where two agents choose actions in turn and one agent wants pirical Nash equilibrium strategy is an approxi- to maximize the total reward while the other wants to min- mate Nash equilibrium strategy in the true TBSG imize it. As a zero-sum game, TBSG is known to have and give both problem-dependent and problem- Nash equilibrium strategy [Shapley, 1953], which means independent bound. -
Political Game Theory Nolan Mccarty Adam Meirowitz
Political Game Theory Nolan McCarty Adam Meirowitz To Liz, Janis, Lachlan, and Delaney. Contents Acknowledgements vii Chapter 1. Introduction 1 1. Organization of the Book 2 Chapter 2. The Theory of Choice 5 1. Finite Sets of Actions and Outcomes 6 2. Continuous Outcome Spaces* 10 3. Utility Theory 17 4. Utility representations on Continuous Outcome Spaces* 18 5. Spatial Preferences 19 6. Exercises 21 Chapter 3. Choice Under Uncertainty 23 1. TheFiniteCase 23 2. Risk Preferences 32 3. Learning 37 4. Critiques of Expected Utility Theory 41 5. Time Preferences 46 6. Exercises 50 Chapter 4. Social Choice Theory 53 1. The Open Search 53 2. Preference Aggregation Rules 55 3. Collective Choice 61 4. Manipulation of Choice Functions 66 5. Exercises 69 Chapter 5. Games in the Normal Form 71 1. The Normal Form 73 2. Solutions to Normal Form Games 76 3. Application: The Hotelling Model of Political Competition 83 4. Existence of Nash Equilibria 86 5. Pure Strategy Nash Equilibria in Non-Finite Games* 93 6. Application: Interest Group Contributions 95 7. Application: International Externalities 96 iii iv CONTENTS 8. Computing Equilibria with Constrained Optimization* 97 9. Proving the Existence of Nash Equilibria** 98 10. Strategic Complementarity 102 11. Supermodularity and Monotone Comparative Statics* 103 12. Refining Nash Equilibria 108 13. Application: Private Provision of Public Goods 109 14. Exercises 113 Chapter 6. Bayesian Games in the Normal Form 115 1. Formal Definitions 117 2. Application: Trade restrictions 119 3. Application: Jury Voting 121 4. Application: Jury Voting with a Continuum of Signals* 123 5. Application: Public Goods and Incomplete Information 126 6. -
Discovery and Equilibrium in Games with Unawareness∗
Discovery and Equilibrium in Games with Unawareness∗ Burkhard C. Schippery April 20, 2018 Abstract Equilibrium notions for games with unawareness in the literature cannot be interpreted as steady-states of a learning process because players may discover novel actions during play. In this sense, many games with unawareness are \self-destroying" as a player's representa- tion of the game may change after playing it once. We define discovery processes where at each state there is an extensive-form game with unawareness that together with the players' play determines the transition to possibly another extensive-form game with unawareness in which players are now aware of actions that they have discovered. A discovery process is rationalizable if players play extensive-form rationalizable strategies in each game with un- awareness. We show that for any game with unawareness there is a rationalizable discovery process that leads to a self-confirming game that possesses a self-confirming equilibrium in extensive-form rationalizable strategies. This notion of equilibrium can be interpreted as steady-state of both a discovery and learning process. Keywords: Self-confirming equilibrium, conjectural equilibrium, extensive-form rational- izability, unawareness, extensive-form games, equilibrium, learning, discovery. JEL-Classifications: C72, D83. ∗I thank Aviad Heifetz, Byung Soo Lee, and seminar participants at UC Berkeley, the University of Toronto, the Barcelona workshop on Limited Reasoning and Cognition, SAET 2015, CSLI 2016, TARK 2017, and the Virginia Tech Workshop on Advances in Decision Theory 2018 for helpful discussions. An abbreviated earlier version appeared in the online proceedings of TARK 2017 under the title “Self-Confirming Games: Unawareness, Discovery, and Equilibrium".