TY - GEN
T1 - Ensemble evolution of checkers players with knowledge of opening, middle and endgame
AU - Kim, Kyung Joong
AU - Cho, Sung Bae
PY - 2006
Y1 - 2006
N2 - In this paper, we argue that the insertion of domain knowledge into ensemble of diverse evolutionary checkers can produce improved strategies and reduce evolution time by restricting search space. The evolutionary approach for game is different from the traditional one that exploits knowledge of the opening, middle, and endgame stages, so that it is not sometimes efficient to evolve simple heuristic that is found easily by humans because it is based purely on a bottom-up style of construction. In this paper, we have proposed the systematic insertion of opening knowledge and an endgame database into the framework of evolutionary checkers. Also, common knowledge, the combination of diverse strategies is better than the single best one, is inserted into the middle stage and is implemented using crowding algorithm and a strategy combination scheme. Experimental results show that the proposed method is promising for generating better strategies.
AB - In this paper, we argue that the insertion of domain knowledge into ensemble of diverse evolutionary checkers can produce improved strategies and reduce evolution time by restricting search space. The evolutionary approach for game is different from the traditional one that exploits knowledge of the opening, middle, and endgame stages, so that it is not sometimes efficient to evolve simple heuristic that is found easily by humans because it is based purely on a bottom-up style of construction. In this paper, we have proposed the systematic insertion of opening knowledge and an endgame database into the framework of evolutionary checkers. Also, common knowledge, the combination of diverse strategies is better than the single best one, is inserted into the middle stage and is implemented using crowding algorithm and a strategy combination scheme. Experimental results show that the proposed method is promising for generating better strategies.
UR - http://www.scopus.com/inward/record.url?scp=33749573928&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33749573928&partnerID=8YFLogxK
U2 - 10.1007/11801603_112
DO - 10.1007/11801603_112
M3 - Conference contribution
AN - SCOPUS:33749573928
SN - 3540366679
SN - 9783540366676
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 950
EP - 954
BT - PRICAI 2006
PB - Springer Verlag
T2 - 9th Pacific Rim International Conference on Artificial Intelligence
Y2 - 7 August 2006 through 11 August 2006
ER -