Using Correlated Strategies for Computing Stackelberg Equilibria in Extensive-Form Games

被引:0
|
作者
Cermak, Jiri [1 ]
Bosansky, Branislav [1 ,2 ]
Durkota, Karel [1 ]
Lisy, Viliam [1 ,3 ]
Kiekintveld, Christopher [4 ]
机构
[1] Czech Tech Univ, Fac Elect Engn, Agent Technol Ctr, Prague, Czech Republic
[2] Aarhus Univ, Dept Comp Sci, Aarhus, Denmark
[3] Univ Alberta, Dept Comp Sci, Edmonton, AB, Canada
[4] Univ Texas El Paso, Dept Comp Sci, El Paso, TX 79968 USA
基金
新加坡国家研究基金会; 美国国家科学基金会;
关键词
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
Strong Stackelberg Equilibrium (SSE) is a fundamental solution concept in game theory in which one player commits to a strategy, while the other player observes this commitment and plays a best response. We present a new algorithm for computing SSE for two-player extensive-form general-sum games with imperfect information (EFGs) where computing SSE is an NP-hard problem. Our algorithm is based on a correlated version of SSE, known as Stackelberg Extensive Form Correlated Equilibrium (SEFCE). Our contribution is therefore twofold: (1) we give the first linear program for computing SEFCE in EFGs without chance, (2) we repeatedly solve and modify this linear program in a systematic search until we arrive to SSE. Our new algorithm outperforms the best previous algorithms by several orders of magnitude.
引用
收藏
页码:439 / 445
页数:7
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