The Complexity of Infinitely Repeated Alternating Move Games
Yaron Velner

TL;DR
This paper explores the computational complexity of infinite alternating move games, establishing connections to mean-payoff games and providing approximation algorithms for social welfare optimization.
Contribution
It proves polynomial equivalence between finding exact equilibria in two-player zero-sum games and solving mean-payoff games, and introduces an FPTAS for social welfare-optimized approximate equilibria.
Findings
Exact equilibrium computation is polynomial-time equivalent to mean-payoff game solving.
Pure strategies can achieve optimal social welfare in approximate equilibria.
An FPTAS exists for social welfare-approximate equilibria in alternating move games.
Abstract
We consider infinite duration alternating move games. These games were previously studied by Roth, Balcan, Kalai and Mansour. They presented an FPTAS for computing an approximated equilibrium, and conjectured that there is a polynomial algorithm for finding an exact equilibrium. We extend their study in two directions: (1) We show that finding an exact equilibrium, even for two-player zero-sum games, is polynomial time equivalent to finding a winning strategy for a (two-player) mean-payoff game on graphs. The existence of a polynomial algorithm for the latter is a long standing open question in computer science. Our hardness result for two-player games suggests that two-player alternating move games are harder to solve than two-player simultaneous move games, while the work of Roth et al., suggests that for , -player games are easier to analyze in the alternating move…
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Taxonomy
TopicsGame Theory and Applications · Game Theory and Voting Systems · Markov Chains and Monte Carlo Methods
