An epistemic approach to stochastic games

In this paper we focus on stochastic games with finitely many states and actions. For this setting we study the epistemic concept of common belief in future rationality, which is based on the condition that players always believe that their opponents will choose rationally in the future. We distinguish two different versions of the concept—one for the discounted case with a fixed discount factor $$\delta ,$$δ, and one for the case of uniform optimality, where optimality is required for all discount factors close enough to 1” . We show that both versions of common belief in future rationality are always possible in every stochastic game, and always allow for stationary optimal strategies. That is, for both versions we can always find belief hierarchies that express common belief in future rationality, and that have stationary optimal strategies. We also provide an epistemic characterization of subgame perfect equilibrium for two-player stochastic games, showing that it is equivalent to mutual belief in future rationality together with some “correct beliefs assumption”.

[1]  Andrés Perea,et al.  Belief in the opponents' future rationality , 2014, Games Econ. Behav..

[2]  Ronald A. Howard,et al.  Dynamic Programming and Markov Processes , 1960 .

[3]  Jonathan A. Zvesper,et al.  Keep ‘hoping’ for rationality: a solution to the backward induction paradox , 2009, Synthese.

[4]  Marciano M. Siniscalchi,et al.  Hierarchies of Conditional Beliefs and Interactive Epistemology in Dynamic Games , 1999 .

[5]  R. Aumann,et al.  Epistemic Conditions for Nash Equilibrium , 1995 .

[6]  Andrés Perea,et al.  Backward Induction versus Forward Induction Reasoning , 2010, Games.

[7]  Pierpaolo Battigalli,et al.  Strong Belief and Forward Induction Reasoning , 2002, J. Econ. Theory.

[8]  Antonio Penta Robust dynamic implementation , 2015, J. Econ. Theory.

[9]  J. Filar,et al.  Competitive Markov Decision Processes , 1996 .

[10]  Adam Brandenburger,et al.  Rationalizability and Correlated Equilibria , 1987 .

[11]  Elchanan Ben-Porath,et al.  Rationality, Nash Equilibrium and Backwards Induction in Perfect-Information Games , 1997 .

[12]  John C. Harsanyi,et al.  Games with Incomplete Information Played by "Bayesian" Players, I-III: Part I. The Basic Model& , 2004, Manag. Sci..

[13]  Andrés Perea,et al.  A one-person doxastic characterization of Nash strategies , 2007, Synthese.

[14]  T. Tan,et al.  The Bayesian foundations of solution concepts of games , 1988 .

[15]  D. Blackwell,et al.  THE BIG MATCH , 1968, Classics in Game Theory.

[16]  J. Harsanyi Games with Incomplete Information Played by “Bayesian” Players Part II. Bayesian Equilibrium Points , 1968 .

[17]  Antonio Penta,et al.  Robust Dynamic Mechanism Design , 2011 .

[18]  J. Nash,et al.  NON-COOPERATIVE GAMES , 1951, Classics in Game Theory.

[19]  Dean Gillette,et al.  9. STOCHASTIC GAMES WITH ZERO STOP PROBABILITIES , 1958 .

[20]  R. Rosenthal Games of perfect information, predatory pricing and the chain-store paradox , 1981 .

[21]  John F. Nash,et al.  EQUILIBRIUM POINTS IN 𝑛-PERSON GAMES , 2020 .

[22]  D. Blackwell Discrete Dynamic Programming , 1962 .

[23]  A. Perea Epistemic Game Theory: Reasoning and Choice , 2012 .

[24]  Amanda Friedenberg,et al.  When do type structures contain all hierarchies of beliefs? , 2010, Games Econ. Behav..

[25]  J. Harsanyi Games with Incomplete Information Played by 'Bayesian' Players, Part III. The Basic Probability Distribution of the Game , 1968 .

[26]  J. Nash Equilibrium Points in N-Person Games. , 1950, Proceedings of the National Academy of Sciences of the United States of America.

[27]  Adam Brandenburger,et al.  The Role of Common Knowledge Assumptions in Game Theory , 1989 .

[28]  L. Shapley,et al.  Stochastic Games* , 1953, Proceedings of the National Academy of Sciences.

[29]  Geir B. Asheim The Consistent Preferences Approach to Deductive Reasoning in Games , 2005 .