Billiards is a game of both strategy and physical skill. To succeed, a player must be able to select strong shots, and then execute them accurately and consistently. Several robotic billiards players have recently been developed. These systems address the task of executing shots on a physical table, but so far have incorporated little strategic reasoning. They require AI to select the ‘best’ shot taking into account the accuracy of the robotics, the noise inherent in the domain, the continuous nature of the search space, the difﬁculty of the shot, and the goal of maximizing the chances of winning. This paper develops and compares several approaches to establishing a strong AI for billiards. The resulting program, PickPocket, won the ﬁrst international computer billiards competition.
Title: Running the Table: An AI for Computer Billiards
Author: Michael Smith
Department of Computing Science, University of Alberta
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