@unpublished{upm20977,
           title = {Evolving and coevolving computer go players using neuroevolution.},
            note = {Unpublished},
       booktitle = {COPCOM 2011 1st International Workshop on Coping with Complexity},
            year = {2011},
             url = {http://www.complexity2011.org},
          author = {Zela Moraya, Wester Edison and Zato Recellado, Jose Gabriel},
        keywords = {Go, evolution, Coevolution, Neuroevolution, SANE, SANEi, Evoluci{\'o}n, Coevoluci{\'o}n, Neuroevoluci{\'o}n.},
        abstract = {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.}
}