Blackman, ToddAgah, Arvin2016-01-292016-01-292011Blackman, Todd, and Arvin Agah. "A Multi-Agent Approach to the Game of Go Using Genetic Algorithms." Journal of Intelligent Systems 18.1-2 (2011): n. pag. http://dx.doi.org/10.1515/JISYS.2009.18.1-2.143.https://hdl.handle.net/1808/19816This is the published version. Copyright De GruyterMany researchers have written or attempted to write programs that play the ancient Chinese board game called Go. Although some programs play the game quite well compared with beginners, few play extremely well, and none of the best programs rely on soft computing artificial intelligence techniques like genetic algorithms or neural networks. This paper explores the advantages and possibilities of using genetic algorithms to evolve a multiagent Go player. We show that although individual agents may play poorly, collectively the agents working together play the game significantly better.Game of GoGenetic algorithmsMulti-agent systemsArticle10.1515/JISYS.2009.18.1-2.143openAccess