TY  - UNPB
ID  - upm20977
M2  - Oct 19, 2011 - Oct 20, 2011
TI  - Evolving and coevolving computer go players using neuroevolution.
N1  - Unpublished
N2  - 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.
UR  - http://www.complexity2011.org
Y1  - 2011///
AV  - public
A1  - Zela Moraya, Wester Edison
A1  - Zato Recellado, Jose Gabriel
KW  - Go
KW  -  evolution
KW  -  Coevolution
KW  -  Neuroevolution
KW  -  SANE
KW  -  SANEi
KW  -  Evolución
KW  -  Coevolución
KW  -  Neuroevolución.
T2  - COPCOM 2011 1st International Workshop on Coping with Complexity
EP  - 10
ER  -