title: Evolving and coevolving computer go players using neuroevolution.
creator: Zela Moraya, Wester Edison
creator: Zato Recellado, Jose Gabriel
subject: Computer Science
description: The Go game is ancient very complex game with simple rules which still is a challenge for the AI.This work cover some neuroevolution techniques used in reinforcement learning applied to the GO game as SANE (Symbiotic Adaptive Neuro-Evolution) and presents a variation to this method with the intention of evolving better strategies in the game. The computer Go player based in SANE is evolved againts a knowed player which creates some problem as determinism for which is proposed the co-evolution. Finally, it is introduced an algorithm to co-evolve two populations of neurons to evolve better computer Go players.
publisher: Facultad de Informática (UPM)
rights: https://creativecommons.org/licenses/by-nc-nd/3.0/es/
date: 2011
type: info:eu-repo/semantics/conferenceObject
type: Presentation at Congress or Conference
source:  | COPCOM 2011 1st International Workshop on Coping with Complexity | Cluj-Napoca, Romania | Oct 19, 2011 - Oct 20, 2011
type: PeerReviewed
format: application/pdf
language: eng
relation: http://www.complexity2011.org
rights: info:eu-repo/semantics/openAccess
identifier: https://oa.upm.es/20977/