Asynchronous parallel game-tree search

Abstract

Tree searching is a fundamental and computationally intensive problem in artificial intelligence. Parallelization of tree-searching algorithms is one method of improving the speed of these algorithms. However, a high-performance parallel two-player game-tree search algorithm has eluded researchers. Most parallel game-tree search approaches follow synchronous methods, where the work is concentrated within a specific part of the tree, or a given search depth. This thesis shows that asynchronous game-tree search algorithms can be as efficient as synchronous methods in determining the minimax value. A taxonomy of previous work in parallel game-tree search is presented. A theoretical model is developed for comparing the efficiency of synchronous and asynchronous search algorithms under realistic assumptions. APHID, a portable parallel game-tree search library, has been built based on the asynchronous parallel game-tree search algorithm proposed in the comparison. The library is easy to implement into a sequential game-tree searching program. APHID has been added to four programs written by different authors. APHID yields better observed speedups than synchronous search methods for an Othello and a checkers program, and yields comparable observed speedups to synchronous methods on two chess programs.