Study and Improvement of Search Algorithms in Multi-Player Perfect-Information Games

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteur principal: Cohen-Solal, Quentin
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911605650882560
author Cohen-Solal, Quentin
author_facet Cohen-Solal, Quentin
contents In this article, we generalize Unbounded Minimax, the state-of-the-art search algorithm for zero sums two-player games with perfect information to the framework of multiplayer games with perfect information. We experimentally show that this generalized algorithm also achieves better performance than the main multiplayer search algorithms.
format Preprint
id arxiv_https___arxiv_org_abs_2604_17378
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Study and Improvement of Search Algorithms in Multi-Player Perfect-Information Games
Cohen-Solal, Quentin
Computer Science and Game Theory
Artificial Intelligence
In this article, we generalize Unbounded Minimax, the state-of-the-art search algorithm for zero sums two-player games with perfect information to the framework of multiplayer games with perfect information. We experimentally show that this generalized algorithm also achieves better performance than the main multiplayer search algorithms.
title Study and Improvement of Search Algorithms in Multi-Player Perfect-Information Games
topic Computer Science and Game Theory
Artificial Intelligence
url https://arxiv.org/abs/2604.17378