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Econometrica Vol. 88 No. 4 2020

Algorithms for Stochastic Games With Perfect Monitoring

Dilip Abreu1; B. A. Brooks2; Yuliy Sannikov3

1 Department of Economics, New York University · 2 Department of Economics, University of Chicago. · 3 Graduate School of Business, Stanford University

open access

Abstract

We study the pure‐strategy subgame‐perfect Nash equilibria of stochastic games with perfect monitoring, geometric discounting, and public randomization. We develop novel algorithms for computing equilibrium payoffs, in which we combine policy iteration when incentive constraints are slack with value iteration when incentive constraints bind. We also provide software implementations of our algorithms. Preliminary simulations indicate that they are significantly more efficient than existing methods. The theoretical results that underlie the algorithms also imply bounds on the computational complexity of equilibrium payoffs when there are two players. When there are more than two players, we show by example that the number of extreme equilibrium payoffs may be countably infinite.

DOI
10.3982/ecta14357
Volume
88
Issue
4
Pages
1661-1695
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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