Symbolic Classification of General Two-Player Games

Authors:
Stefan Edelkamp;Peter Kissmann
Affiliations:
Fakultät für Informatik, Technische Universität Dortmund, Dortmund, Germany D-44227;Fakultät für Informatik, Technische Universität Dortmund, Dortmund, Germany D-44227
Venue:
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Year:
2008

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Abstract

In this paper we present a new symbolic algorithm for the classification, i. e. the calculation of the rewards for both players in case of optimal play, of two-player games with general rewards according to the Game Description Language. We will show that it classifies all states using a linear number of images concerning the depth of the game graph. We also present an extension that uses this algorithm to create symbolic endgame databases and then performs UCT to find an estimate for the classification of the game.