The board game surakarta has been played at the icga computer olympiad since 2007. In this paper the ideas behind the agent sia, which won the competition five times, are revealed. The paper describes its aß \alpha \beta -based variable-depth search mechanism. Search enhancements such as multi-cut forward pruning and realization probability search are shown to improve the agent considerably. Additionally, features of the static evaluation function are presented. Experimental results indicate that features, which reward distribution of the pieces and penalize pieces that clutter together, give a genuine improvement in the playing strength.
|Communications in Computer and Information Science