Best-First and Depth-First Minimax Search in Practice

May 07, 2015 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Aske Plaat, Jonathan Schaeffer, Wim Pijls, Arie de Bruin arXiv ID 1505.01603 Category cs.AI: Artificial Intelligence Citations 5 Venue arXiv.org Last Checked 4 months ago
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.
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