On the Approximation of Nash Equilibria in Sparse Win-Lose Games

被引：0

作者：

Liu, Zhengyang ^{[1
]}

Sheng, Ying ^{[2
]}

机构：

[1] Shanghai Jiao Tong Univ, Shanghai, Peoples R China

[2] Columbia Univ, New York, NY 10027 USA

来源：

THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE | 2018年

关键词：

COMPLEXITY; POINTS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We show that the problem of finding an approximate Nash equilibrium with a polynomial precision is PPAD-hard even for two-player sparse win-lose games (i.e., games with {0, 1}-entries such that each row and column of the two n x n payoff matrices have at most O(log n) many ones). The proof is mainly based on a new class of prototype games called Chasing Games, which we think is of independent interest in understanding the complexity of Nash equilibrium.

引用

页码：1154 / 1160

页数：7

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