collaborators

8 papers

cs.GT2026

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

Quentin Cohen-Solal

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 game…

cs.AI2026

Completeness of Unbounded Best-First Minimax and Descent Minimax

Quentin Cohen-Solal

In this article, we focus on search algorithms for two-player perfect information games, whose objective is to determine the best possible strategy, and ideally a winning strategy.…

cs.AI2026

Minibal: Balanced Game-Playing Without Opponent Modeling

Quentin Cohen-Solal, Tristan Cazenave

Recent advances in game AI, such as AlphaZero and Athénan, have achieved superhuman performance across a wide range of board games. While highly powerful, these agents are ill-sui…

cs.AI2026

Deciding the Satisfiability of Combined Qualitative Constraint Networks

Quentin Cohen-Solal, Alexandre Niveau, Maroua Bouzid

Among the various forms of reasoning studied in the context of artificial intelligence, qualitative reasoning makes it possible to infer new knowledge in the context of imprecise,…

cs.AI2025

On some improvements to Unbounded Minimax

Quentin Cohen-Solal, Tristan Cazenave

This paper presents the first experimental evaluation of four previously untested modifications of Unbounded Best-First Minimax algorithm. This algorithm explores the game tree by…

cs.AI2025

Learning to Play Two-Player Perfect-Information Games without Knowledge

Quentin Cohen-Solal

In this paper, several techniques for learning game state evaluation functions by reinforcement are proposed. The first is a generalization of tree bootstrapping (tree learning): i…