Similarity-Based Retrieval and Solution Re-use Policies in the Game of Texas Hold'em

摘要

In previous papers we have presented our autonomous poker playing agent (SARTRE) that uses a memory-based approach to create a betting strategy for two-player, limit Texas Hold'em. SARTRE participated in the 2009 IJCAI Computer Poker Competition where the system was thoroughly evaluated by challenging a range of other computerised opponents. Since the competition SARTRE has undergone case-based maintenance. In this paper we present results from the 2009 Computer Poker Competition and describe the latest modifications and improvements to the system. Specifically, we investigate two claims: the first that modifying the solution representation results in changes to the problem coverage and the second that different policies for re-using solutions leads to changes in performance. Three separate solution re-use policies for making betting decisions are introduced and evaluated. We conclude by presenting results of self-play experiments between the pre and post maintenance systems.