The computational complexity of Nash equilibria in concisely represented games

Citation:

Schoenebeck, Grant, and Salil Vadhan. “The computational complexity of Nash equilibria in concisely represented games.” ACM Transactions on Computation Theory 4, no. 2 (2012).
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Abstract:

Version History: Preliminary versions as ECCC TOR05-52 (https://eccc.weizmann.ac.il/report/2005/052/; attached as ECCC2005.pdf) and in EC '06 (https://dl.acm.org/doi/10.1145/1134707.1134737; attached as EC2006.pdf).

Games may be represented in many different ways, and different representations of games affect the complexity of problems associated with games, such as finding a Nash equilibrium. The traditional method of representing a game is to explicitly list all the payoffs, but this incurs an exponential blowup as the number of agents grows. We study two models of concisely represented games: circuit games, where the payoffs are computed by a given boolean circuit, and graph games, where each agent’s payoff is a function of only the strategies played by its neighbors in a given graph. For these two models, we study the complexity of four questions: determining if a given strategy is a Nash equilibrium, finding a Nash equilibrium, determining if there exists a pure Nash equilibrium, and determining if there exists a Nash equilibrium in which the payoffs to a player meet some given guarantees. In many cases, we obtain tight results, showing that the problems are complete for various complexity classes.

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Last updated on 06/03/2020