Study and improvement of search algorithms in two-players perfect information games

TL;DR

This paper evaluates various search algorithms for two-player perfect information games, introduces a new algorithm, and demonstrates its superior performance across multiple games and search times.

Contribution

It provides the first comprehensive evaluation of search algorithms' generality and introduces a novel algorithm that outperforms existing methods in various scenarios.

Findings

New algorithm outperforms existing algorithms in short search times.

Proposed algorithm outperforms others in 17 of 22 games at medium search times.

Study highlights the variability of algorithm performance across different games.

Abstract

Games, in their mathematical sense, are everywhere (game industries, economics, defense, education, chemistry, biology, ...).Search algorithms in games are artificial intelligence methods for playing such games. Unfortunately, there is no study on these algorithms that evaluates the generality of their performance. We propose to address this gap in the case of two-player zero-sum games with perfect information. Furthermore, we propose a new search algorithm and we show that, for a short search time, it outperforms all studied algorithms on all games in this large experiment and that, for a medium search time, it outperforms all studied algorithms on 17 of the 22 studied games.