Reputation and Equilibrium Characterization in Repeated Games with Conflicting Interests
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Repeated Games
6.254 : Game Theory with Engineering Applications Lecture 15: Repeated Games Asu Ozdaglar MIT April 1, 2010 1 Game Theory: Lecture 15 Introduction Outline Repeated Games (perfect monitoring) The problem of cooperation Finitely-repeated prisoner's dilemma Infinitely-repeated games and cooperation Folk Theorems Reference: Fudenberg and Tirole, Section 5.1. 2 Game Theory: Lecture 15 Introduction Prisoners' Dilemma How to sustain cooperation in the society? Recall the prisoners' dilemma, which is the canonical game for understanding incentives for defecting instead of cooperating. Cooperate Defect Cooperate 1, 1 −1, 2 Defect 2, −1 0, 0 Recall that the strategy profile (D, D) is the unique NE. In fact, D strictly dominates C and thus (D, D) is the dominant equilibrium. In society, we have many situations of this form, but we often observe some amount of cooperation. Why? 3 Game Theory: Lecture 15 Introduction Repeated Games In many strategic situations, players interact repeatedly over time. Perhaps repetition of the same game might foster cooperation. By repeated games, we refer to a situation in which the same stage game (strategic form game) is played at each date for some duration of T periods. Such games are also sometimes called \supergames". We will assume that overall payoff is the sum of discounted payoffs at each stage. Future payoffs are discounted and are thus less valuable (e.g., money and the future is less valuable than money now because of positive interest rates; consumption in the future is less valuable than consumption now because of time preference). We will see in this lecture how repeated play of the same strategic game introduces new (desirable) equilibria by allowing players to condition their actions on the way their opponents played in the previous periods. -
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 .................................. -
Finitely Repeated Games
Repeated games 1: Finite repetition Universidad Carlos III de Madrid 1 Finitely repeated games • A finitely repeated game is a dynamic game in which a simultaneous game (the stage game) is played finitely many times, and the result of each stage is observed before the next one is played. • Example: Play the prisoners’ dilemma several times. The stage game is the simultaneous prisoners’ dilemma game. 2 Results • If the stage game (the simultaneous game) has only one NE the repeated game has only one SPNE: In the SPNE players’ play the strategies in the NE in each stage. • If the stage game has 2 or more NE, one can find a SPNE where, at some stage, players play a strategy that is not part of a NE of the stage game. 3 The prisoners’ dilemma repeated twice • Two players play the same simultaneous game twice, at ! = 1 and at ! = 2. • After the first time the game is played (after ! = 1) the result is observed before playing the second time. • The payoff in the repeated game is the sum of the payoffs in each stage (! = 1, ! = 2) • Which is the SPNE? Player 2 D C D 1 , 1 5 , 0 Player 1 C 0 , 5 4 , 4 4 The prisoners’ dilemma repeated twice Information sets? Strategies? 1 .1 5 for each player 2" for each player D C E.g.: (C, D, D, C, C) Subgames? 2.1 5 D C D C .2 1.3 1.5 1 1.4 D C D C D C D C 2.2 2.3 2 .4 2.5 D C D C D C D C D C D C D C D C 1+1 1+5 1+0 1+4 5+1 5+5 5+0 5+4 0+1 0+5 0+0 0+4 4+1 4+5 4+0 4+4 1+1 1+0 1+5 1+4 0+1 0+0 0+5 0+4 5+1 5+0 5+5 5+4 4+1 4+0 4+5 4+4 The prisoners’ dilemma repeated twice Let’s find the NE in the subgames. -
Strong Enforcement by a Weak Authority∗
Strong Enforcement by a Weak Authority¤ Jakub Steinery CERGE-EI February 17, 2006 Abstract This paper studies the enforcement abilities of authorities with a limited commitment to punishing violators. Commitment of resources su±cient to punish only one agent is needed to enforce high compliance of an arbitrary number of agents. Though existence of other, non-compliance equilibria is generally inevitable, there exist punishment rules suitable for a limited authority to assure that compliance prevails in the long run under stochastic evolution. JEL classi¯cation: C73, D64, H41. Keywords: Commitment, Enforcement, Punishment, Stochastic Evolution. ¤The paper builds on my earlier work \A Trace of Anger is Enough, on the Enforcement of Social Norms". I bene¯ted from the comments of Kenneth Binmore, Fuhito Kojima, Simon GÄachter, Werner GÄuth,Eugen Kov¶a·c,and Jarom¶³rKova·r¶³k.Dirk Engelmann, Andreas Ortmann, and Avner Shaked inspired me in numerous discussions. Laura Strakova carefully edited the paper. The usual disclaimer applies. yCenter for Economic Research and Graduate Education, Charles University, and Economics Institute, Academy of Sciences of the Czech Republic (CERGE-EI), Address: Politickych Veznu 7, 111 21, Prague, Czech Republic, Tel: +420-605-286-947, E-mail: [email protected]. WWW: http://home.cerge-ei.cz/steiner/ 1 1 Introduction Centralized authorities, such as governments, or decentralized ones, such as peers, use threats of punishment to enforce norms. However the authority, whether centralized or decentralized, achieves compliance only if it is able to commit to the punishment threat. Punishment is often costly, and hence an important determinant of the authority's success at enforcement is the amount of resources committed for punishment. -
California Institute of Technology Pasadena, California 91125
DIVISION OF THE HUMANITIES AND SOCIAL SCIENCES CALIFORNIA INSTITUTE OF TECHNOLOGY PASADENA, CALIFORNIA 91125 A BARGAINING MODEL OF LEGISLATIVE POLICY-MAKING Jeffrey S. Banks California Institute of Technology John Duggan University of Rochester I T U T E O T F S N T I E C A I H N N R O O 1891 L F O I L G A Y C SOCIAL SCIENCE WORKING PAPER 1162 May 2003 A Bargaining Model of Legislative Policy-making Jeffrey S. Banks John Duggan Abstract We present a general model of legislative bargaining in which the status quo is an arbitrary point in a multidimensional policy space. In contrast to other bargaining mod- els, the status quo is not assumed to be “bad,” and delay may be Pareto efficient. We prove existence of stationary equilibria. The possibility of equilibrium delay depends on four factors: risk aversion of the legislators, the dimensionality of the policy space, the voting rule, and the possibility of transfers across districts. If legislators are risk averse, if there is more than one policy dimension, and if voting is by majority rule, for example, then delay will almost never occur. In one dimension, delay is possible if and only if the status quo lies in the core of the voting rule, and then it is the only possible outcome. This “core selection” result yields a game-theoretic foundation for the well-known median voter theorem. Our comparative statics analysis yield two noteworthy insights: (i) if the status quo is close to the core, then equilibrium policy outcomes will also be close to the core (a moderate status quo produces moderate policy outcomes), and (ii) if legislators are patient, then equilibrium proposals will be close to the core (legislative patience leads to policy moderation). -
The Artificial Cold War Content of Game Theory and Operations Research Richard Vahrenkamp [University of Kassel, Germany]
real-world economics review, issue no. 88 subscribe for free Nominal science without data – the artificial Cold War content of Game Theory and Operations Research Richard Vahrenkamp [University of Kassel, Germany] Copyright: Richard Vahrenkamp 2019 You may post comments on this paper at https://rwer.wordpress.com/comments-on-rwer-issue-no-88/ Abstract Expanding upon literature on early digital computers, this paper shows the role mathematicians have undertaken in founding the academic fields of Game Theory and Operations Research, and details how they were supported by the mathematics departments of military agencies in branches of the US Armed Services. This paper claims that application is only decoration. Other than astronomy, physics and engineering, where experiments generate data analysed with the aid of models and appropriate software on computers, Game Theory and Operations Research are not data driven but method driven and remain a branch of applied mathematics. They use the method of “abstractification” in economy and society to derive their models but lack a layer of empirical research needed to generate data and to apply their methods in economics and society. Therefore, their models were only nominal mathematics without application. Introduction Since 1945, the United States had experienced a unique innovation push with the computer, the nuclear weapon, new air combat weapons and the transistor within just a few years. These innovations were accompanied by Game Theory and Operations Research in the academic field. Widely–held is the view that computers supplemented the mathematical concepts of Game Theory and Operations Research and gave these fields a fresh impulse. Together, they established the view of the world as a space of numbers and introduced quantitative methods in economics, political science and in sociology. -
Norms, Repeated Games, and the Role of Law
Norms, Repeated Games, and the Role of Law Paul G. Mahoneyt & Chris William Sanchiricot TABLE OF CONTENTS Introduction ............................................................................................ 1283 I. Repeated Games, Norms, and the Third-Party Enforcement P rob lem ........................................................................................... 12 88 II. B eyond T it-for-Tat .......................................................................... 1291 A. Tit-for-Tat for More Than Two ................................................ 1291 B. The Trouble with Tit-for-Tat, However Defined ...................... 1292 1. Tw o-Player Tit-for-Tat ....................................................... 1293 2. M any-Player Tit-for-Tat ..................................................... 1294 III. An Improved Model of Third-Party Enforcement: "D ef-for-D ev". ................................................................................ 1295 A . D ef-for-D ev's Sim plicity .......................................................... 1297 B. Def-for-Dev's Credible Enforceability ..................................... 1297 C. Other Attractive Properties of Def-for-Dev .............................. 1298 IV. The Self-Contradictory Nature of Self-Enforcement ....................... 1299 A. The Counterfactual Problem ..................................................... 1300 B. Implications for the Self-Enforceability of Norms ................... 1301 C. Game-Theoretic Workarounds ................................................ -
Policy Implications of Economic Complexity and Complexity Economics
Munich Personal RePEc Archive Policy Implications of Economic Complexity and Complexity Economics Elsner, Wolfram iino – Institute of Institutional and Innovation Economics, University of Bremen, Faculty of Business Studies and Economics 26 March 2015 Online at https://mpra.ub.uni-muenchen.de/68372/ MPRA Paper No. 68372, posted 15 Dec 2015 10:03 UTC Policy Implications of Economic Complexity. Towards a systemic, long-run, strong, adaptive, and interactive policy conception1 Wolfram Elsner2 Revised, December 11, 2015 Abstract: Complexity economics has developed into a promising cutting-edge research program for a more realistic economics in the last three or four decades. Also some convergent micro- and macro-foundations across heterodox schools have been attained with it. With some time lag, boosted by the financial crisis 2008ff., a surge to explore economic complexity’s (EC) policy implications emerged. It demonstrated flaws of “neoliberal” policy prescriptions mostly derived from the neoclassical mainstream and its relatively simple and teleological equilibrium models. However, most of the complexity-policy literature still remains rather general. Therefore, policy implications of EC are reinvestigated here. EC usually is specified by “Complex Adaptive (Economic) Systems” [CA(E)S], characterized by mechanisms, dynamic and statistical properties such as capacities of “self-organization” of their components (agents), structural “emergence”, and some statistical distributions in their topologies and movements. For agent-based systems, some underlying “intentionality” of agents, under bounded rationality, includes improving their benefits and reducing the perceived complexity of their decision situations, in an evolutionary process of a population. This includes emergent social institutions. Thus, EC has manifold affinities with long-standing issues of economic heterodoxies, such as uncertainty or path- dependent and idiosyncratic process. -
Strength in Numbers: the Rising of Academic Statistics Departments In
Agresti · Meng Agresti Eds. Alan Agresti · Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics DepartmentsStatistics in the U.S. Rising of Academic The in Numbers: Strength Statistics Departments in the U.S. Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. Alan Agresti • Xiao-Li Meng Editors Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. 123 Editors Alan Agresti Xiao-Li Meng Department of Statistics Department of Statistics University of Florida Harvard University Gainesville, FL Cambridge, MA USA USA ISBN 978-1-4614-3648-5 ISBN 978-1-4614-3649-2 (eBook) DOI 10.1007/978-1-4614-3649-2 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2012942702 Ó Springer Science+Business Media New York 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. -
(Public Section) Padma Awards Directory (1954-2009) Year-Wise List Sl
MINISTRY OF HOME AFFAIRS (Public Section) Padma Awards Directory (1954-2009) Year-Wise List Sl. Prefix First Name Last Name Award State Field Remarks 1954 1 Dr. Sarvapalli Radhakrishnan BR TN Public Affairs Expired 2 Shri Chakravarti Rajagopalachari BR TN Public Affairs Expired 3 Dr. Chandrasekhara Raman BR TN Science & Eng. Expired Venkata 4 Shri Nand Lal Bose PV WB Art Expired 5 Dr. Satyendra Nath Bose PV WB Litt. & Edu. 6 Dr. Zakir Hussain PV AP Public Affairs Expired 7 Shri B.G. Kher PV MAH Public Affairs Expired 8 Shri V.K. Krishna Menon PV KER Public Affairs Expired 9 Shri Jigme Dorji Wangchuk PV BHU Public Affairs 10 Dr. Homi Jehangir Bhabha PB MAH Science & Eng. Expired 11 Dr. Shanti Swarup Bhatnagar PB UP Science & Eng. Expired 12 Shri Mahadeva Iyer Ganapati PB OR Civil Service 13 Dr. J.C. Ghosh PB WB Science & Eng. Expired 14 Shri Maithilisharan Gupta PB UP Litt. & Edu. Expired 15 Shri Radha Krishan Gupta PB DEL Civil Service Expired 16 Shri R.R. Handa PB PUN Civil Service Expired 17 Shri Amar Nath Jha PB UP Litt. & Edu. Expired 18 Shri Malihabadi Josh PB DEL Litt. & Edu. 19 Dr. Ajudhia Nath Khosla PB DEL Science & Eng. Expired 20 Shri K.S. Krishnan PB TN Science & Eng. Expired 21 Shri Moulana Hussain Madni PB PUN Litt. & Edu. Ahmed 22 Shri V.L. Mehta PB GUJ Public Affairs Expired 23 Shri Vallathol Narayana Menon PB KER Litt. & Edu. Expired Wednesday, July 22, 2009 Page 1 of 133 Sl. Prefix First Name Last Name Award State Field Remarks 24 Dr. -
Urgent D.B. I Motion Petition for the Monday Dated 11/07/2016 Cr No 1
file:///C:/Users/HCL/Desktop/HTML/2016_07_11_b_m.htm URGENT D.B. I MOTION PETITION FOR THE MONDAY DATED 11/07/2016 CR NO 1 HON'BLE THE ACTING CHIEF JUSTICE HON'BLE MR. JUSTICE DEEPAK SIBAL 101 CM-7634-CWP-2016 (MINES) RAM SINGH V/S UNION OF INDIA & ORS H.K.BRINDA, AG PUNJAB IN CWP-20640-2015 H.K.BRINDA 102 CWP-13197-2016 (MINES) MEWA RAM V/S STATE OF PUNJAB & ORS S.S.DINARPUR 103 CM-12713-CII-2016 (SAIT) COMMISSIONER OF INCOME TAX CHANDIGARH V/S M/S DENESH GOYAL IMPROVEMENT TRUST MOGA & ITA-147-2016 DENESH GOYAL THE COMMISSIONER OF INCOME TAX CHANDIGARH V/S M/S WITH ITA-133-2016 DENESH GOYAL JALANDHAR IMPROVEMENT TRUST JALANDHAR 104 ITA-27-2016 (SAIT) PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S SURI SONS VIVEK SETHI JALANDHAR CM-1813-CII-2016 VIVEK SETHI PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S HANSA WITH ITA-29-2016 VIVEK SETHI EXPORT CORPORATION JALANDHAR CM-1816-CII-2016 VIVEK SETHI PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S SURI SONS WITH ITA-42-2016 VIVEK SETHI JALANDHAR CM-2805-CII-2016 VIVEK SETHI PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S HANSA WITH ITA-43-2016 VIVEK SETHI EXPORT CORPORATION JALANDHAR CM-2806-CII-2016 VIVEK SETHI PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S HANSA WITH ITA-62-2016 VIVEK SETHI EXPORT CORPORATION JALANDHAR CM-6683-CII-2016 VIVEK SETHI PR COMMISSIONER OF INCOME TAX JALANDHAR V/S M/S SURI SONS WITH ITA-63-2016 VIVEK SETHI JALANDHAR CM-6684-CII-2016 VIVEK SETHI 105 ITA-145-2016 (SAIT) PR COMMISSIONER OF INCOME TAX 2 CHD V/S KIRTI ANAND URVASHI DHUGGA CM-12712-CII-2016 URVASHI DHUGGA 106 ITA-149-2016 (SAIT) PR. -
Lecture Notes
Chapter 12 Repeated Games In real life, most games are played within a larger context, and actions in a given situation affect not only the present situation but also the future situations that may arise. When a player acts in a given situation, he takes into account not only the implications of his actions for the current situation but also their implications for the future. If the players arepatient andthe current actionshavesignificant implications for the future, then the considerations about the future may take over. This may lead to a rich set of behavior that may seem to be irrational when one considers the current situation alone. Such ideas are captured in the repeated games, in which a "stage game" is played repeatedly. The stage game is repeated regardless of what has been played in the previous games. This chapter explores the basic ideas in the theory of repeated games and applies them in a variety of economic problems. As it turns out, it is important whether the game is repeated finitely or infinitely many times. 12.1 Finitely-repeated games Let = 0 1 be the set of all possible dates. Consider a game in which at each { } players play a "stage game" , knowing what each player has played in the past. ∈ Assume that the payoff of each player in this larger game is the sum of the payoffsthat he obtains in the stage games. Denote the larger game by . Note that a player simply cares about the sum of his payoffs at the stage games. Most importantly, at the beginning of each repetition each player recalls what each player has 199 200 CHAPTER 12.