Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games Export

@incollection{HaDa00, abstract = {We present an asymmetric co-evolutionary learning algorithm for imperfect-information zero-sum games. This algorithm is designed so that the fitness of the individual agents is calculated in a way that is compatible with the goal of game-theoretic optimality. This compatibility has been somewhat lacking in previous co-evolutionary approaches, as these have often depended on unwarranted assumptions about the absolute and relative strength of players. Our algorithm design is tested on a game for which the optimal strategy is known, and is seen to work well.}, author = {Halck, Ole M. and Dahl, Fredrik A.}, citeulike-article-id = {2201233}, citeulike-linkout-0 = {http://www.springerlink.com/content/9btb97ly837qnp0g}, journal = {Machine Learning: ECML 2000: 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May/June 2000. Proceedings}, keywords = {co-evolution, minimax, solution\_concept}, pages = {265--279}, posted-at = {2008-01-06 23:51:31}, priority = {5}, title = {Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games}, url = {http://www.springerlink.com/content/9btb97ly837qnp0g}, year = {2000} }

TY - CHAP ID - HaDa00 L3 - citeulike-article-id:2201233 N2 - We present an asymmetric co-evolutionary learning algorithm for imperfect-information zero-sum games. This algorithm is designed so that the fitness of the individual agents is calculated in a way that is compatible with the goal of game-theoretic optimality. This compatibility has been somewhat lacking in previous co-evolutionary approaches, as these have often depended on unwarranted assumptions about the absolute and relative strength of players. Our algorithm design is tested on a game for which the optimal strategy is known, and is seen to work well. JF - Machine Learning: ECML 2000: 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May/June 2000. Proceedings EP - 279 TI - Asymmetric Co-evolution for Imperfect-Information Zero-Sum Games SP - 265 KW - co-evolution KW - minimax KW - solution_concept AU - Halck, Ole AU - Dahl, Fredrik PY - 2000/// UR - http://www.springerlink.com/content/9btb97ly837qnp0g ER -