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Complexity results about Nash equilibria

Publication ,  Journal Article
Conitzer, V; Sandholm, T
Published in: Ijcai International Joint Conference on Artificial Intelligence
December 1, 2003

Noncooperative game theory provides a normative framework for analyzing strategic interactions. However, for the toolbox to be operational, the solutions it defines will have to be computed. In this paper, we provide a single reduction that 1) demonstrates NP-hardness of determining whether Nash equilibria with certain natural properties exist, and 2) demonstrates the #P-hardness of counting Nash equilibria (or connected sets of Nash equilibria). We also show that 3) determining whether a pure-strategy Bayes-Nash equilibrium exists is NP-hard, and that 4) determining whether a pure-strategy Nash equilibrium exists in a stochastic (Markov) game is PSP ACE-hard even if the game is invisible (this remains NP-hard if the game is finite). All of our hardness results hold even if there are only two players and the game is symmetric.

Duke Scholars

Published In

Ijcai International Joint Conference on Artificial Intelligence

ISSN

1045-0823

Publication Date

December 1, 2003

Start / End Page

765 / 771
 

Citation

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Conitzer, V., & Sandholm, T. (2003). Complexity results about Nash equilibria. Ijcai International Joint Conference on Artificial Intelligence, 765–771.
Conitzer, V., and T. Sandholm. “Complexity results about Nash equilibria.” Ijcai International Joint Conference on Artificial Intelligence, December 1, 2003, 765–71.
Conitzer V, Sandholm T. Complexity results about Nash equilibria. Ijcai International Joint Conference on Artificial Intelligence. 2003 Dec 1;765–71.
Conitzer, V., and T. Sandholm. “Complexity results about Nash equilibria.” Ijcai International Joint Conference on Artificial Intelligence, Dec. 2003, pp. 765–71.
Conitzer V, Sandholm T. Complexity results about Nash equilibria. Ijcai International Joint Conference on Artificial Intelligence. 2003 Dec 1;765–771.

Published In

Ijcai International Joint Conference on Artificial Intelligence

ISSN

1045-0823

Publication Date

December 1, 2003

Start / End Page

765 / 771