Plans, Patterns, and Move Categories Guiding a Highly Selective Search

In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move generation to moves in certain move categories to reduce the number of moves considered by the bot significantly. Arimaa is a modern board game that can be played with a standard Chess set. However, the rules of the game are not at all like those of Chess. Furthermore, Arimaa was designed to be as simple and intuitive as possible for humans, yet challenging for computers. While all established Arimaa bots use alpha-beta search with a variety of pruning techniques and other heuristics ending in an extensive positional leaf node evaluation, our new bot, Rat, starts with a positional evaluation of the current position. Based on features found in the current position – supported by pattern matching using a directed position graph – our bot Rat decides which of a given set of plans to follow. The plan then dictate...

• Type: Conference
• Year: 2009
• Where: ACG
• Authors: Gerhard Trippen
• Keywords: ACG 2009, Computer Graphics, Current Position, Pattern Matching, Possible Moves