2 citations · 5 across the 11 of their papers we have counts for
12 papers
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…
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.…
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-suit…
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,…
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…
Study and improvement of search algorithms in two-players perfect information games
Quentin Cohen-Solal
Games, in their mathematical sense, are everywhere (game industries, economics, defense, education, chemistry, biology, ...).Search algorithms in games are artificial intelligence…
The Mathematical Game
Marc Pierre, Quentin Cohen-Solal, Tristan Cazenave
Monte Carlo Tree Search can be used for automated theorem proving. Holophrasm is a neural theorem prover using MCTS combined with neural networks for the policy and the evaluation.…
Learning to Play Stochastic Two-player Perfect-Information Games without Knowledge
Quentin Cohen-Solal, Tristan Cazenave
In this paper, we extend the Descent framework, which enables learning and planning in the context of two-player games with perfect information, to the framework of stochastic game…
Completeness of Unbounded Best-First Game Algorithms
Quentin Cohen-Solal
In this article, we prove the completeness of the following game search algorithms: unbounded best-first minimax with completion and descent with completion, i.e. we show that, wit…
Minimax Strikes Back
Quentin Cohen-Solal, Tristan Cazenave
Deep Reinforcement Learning reaches a superhuman level of play in many complete information games. The state of the art algorithm for learning with zero knowledge is AlphaZero. We…
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…
Tractable Fragments of Temporal Sequences of Topological Information
Quentin Cohen-Solal
In this paper, we focus on qualitative temporal sequences of topological information. We firstly consider the context of topological temporal sequences of length greater than 3 des…