Evolving Mixed Nash Equilibria for Bimatrix Games

被引：0

作者：

Iclanzan, David ^{[1
]}

Noemi, Gasko ^{[1
]}

Dumitrescu, D. ^{[1
]}

机构：

[1] Babes Bolyai Univ, Kogalniceanu 1, Cluj Napoca 400084, Romania

来源：

PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTATION COMPANION (GECCO'12) | 2012年

关键词：

Algorithms; Design; Theory;

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：

In a mixed strategy equilibrium players randomize between their actions according to a very specific probability distribution, even though with regard to the game payoff, they are indifferent between their actions. Currently, there is no compelling model explaining why and how agents may randomize their decisions is such a way, in real world scenarios. In this paper we experiment with a model for bimatrix games, where the goal of the players is to find robust strategies for which the uncertainty in the outcome of the opponent is reduced as much as possible. We show that in an evolutionary setting, the proposed model converges to mixed strategy profiles, if these exist. The result suggest that only local knowledge of the game is sufficient to attain the adaptive convergence.

引用

页码：655 / 656

页数：2