TY - GEN
T1 - Evolving Lose-Checkers players using genetic programming
AU - Benbassat, Amit
AU - Sipper, Moshe
PY - 2010/12/1
Y1 - 2010/12/1
N2 - We present the application of genetic programming (GP) to the zero-sum, deterministic, full-knowledge board game of Lose Checkers. Our system implements strongly typed GP trees, explicitly defined introns, local mutations, and multi-tree individuals. Explicitly defined introns in the genome allow for information selected out of the population to be kept as a reservoir for possible future use. Multi-tree individuals are implemented by a method inspired by structural genes in living organisms, whereby we take a single tree describing a state evaluator and split it.
AB - We present the application of genetic programming (GP) to the zero-sum, deterministic, full-knowledge board game of Lose Checkers. Our system implements strongly typed GP trees, explicitly defined introns, local mutations, and multi-tree individuals. Explicitly defined introns in the genome allow for information selected out of the population to be kept as a reservoir for possible future use. Multi-tree individuals are implemented by a method inspired by structural genes in living organisms, whereby we take a single tree describing a state evaluator and split it.
UR - http://www.scopus.com/inward/record.url?scp=80051946211&partnerID=8YFLogxK
U2 - 10.1109/ITW.2010.5593376
DO - 10.1109/ITW.2010.5593376
M3 - Conference contribution
AN - SCOPUS:80051946211
SN - 9781424462971
T3 - Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG2010
SP - 30
EP - 37
BT - Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG2010
T2 - 2010 IEEE Conference on Computational Intelligence and Games, CIG2010
Y2 - 18 August 2010 through 21 August 2010
ER -