Evolving a roving-eye for go revisited

• Main Author: Mathisen, Bjørn Magnus
• Format: Others
• Language: English
• Published: Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap 2007
• Subjects: ntnudaim; MIT informatikk; Kunstig intelligens og læring
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9527

This thesis presents a further development of Neuroevolution of Augmenting topologies(NEAT)[21]. The author augments NEAT by parallelizing the fitness evaluation of the phenotypes enabling the method to be utilized on highly complex fitness evaluations by running it on a cluster. This augmented version of NEAT is then applied to the inherently complex problem of the Go board game, by using the Gnugo (See www.gnu.org/software/gnugo/.) software package as a fitness evaluator. The performance increase also enables the author to follow up on the predictions of Kenneth Stanley’s previous discussions that co-evolution will help evolve a more general Go player, rather than the predicted evolved behaviour of specializing in beating Gnugo.