Best-First and Depth-First Minimax Search in Practice
Abstract
Most practitioners use a variant of the Alpha-Beta algorithm, a simple depth-first pro- cedure, for searching minimax trees. SSS*, with its best-first search strategy, reportedly offers the potential for more efficient search. However, the complex formulation of the al- gorithm and its alleged excessive memory requirements preclude its use in practice. For two decades, the search efficiency of "smart" best-first SSS* has cast doubt on the effectiveness of "dumb" depth-first Alpha-Beta. This paper presents a simple framework for calling Alpha-Beta that allows us to create a variety of algorithms, including SSS* and DUAL*. In effect, we formulate a best-first algorithm using depth-first search. Expressed in this framework SSS* is just a special case of Alpha-Beta, solving all of the perceived drawbacks of the algorithm. In practice, Alpha-Beta variants typically evaluate less nodes than SSS*. A new instance of this framework, MTD(f), out-performs SSS* and NegaScout, the Alpha-Beta variant of choice by practitioners.
Keywords
Cite
@article{arxiv.1505.01603,
title = {Best-First and Depth-First Minimax Search in Practice},
author = {Aske Plaat and Jonathan Schaeffer and Wim Pijls and Arie de Bruin},
journal= {arXiv preprint arXiv:1505.01603},
year = {2015}
}
Comments
Computer Science in the Netherlands 1995. arXiv admin note: text overlap with arXiv:1404.1515