Win, Lose, or Get Out the Way - Eliminating Unnecessary Evaluation in Game Search

In this paper we present our approach of improving the traditional alpha-beta search process for strategic board games by modifying the method in two ways: 1) forgoing the evaluation of leaf nodes that are not terminal states and 2) employing a utility table that stores the utility for subsets of board configurations. In this paper we concentrate our efforts on the game of Connect Four. Our results have shown significant speed-up, as well as a framework that relaxes common agent assumptions in game search. In addition, it allows game designers to easily modify the agent's strategy by changing the goal from dominance to interaction.

• Type: Conference
• Year: 2008
• Where: FLAIRS
• Authors: Hsiu-Chin Lin, Colleen van Lent
• Keywords: Artificial Intelligence, Common Agent Assumptions, FLAIRS 2008, Strategic Board Games, Traditional Alpha-beta Search