3 papers
cs.AI2025
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…
cs.AI2025
Monte Carlo Graph Coloring
Tristan Cazenave, Benjamin Negrevergne, Florian Sikora
Graph Coloring is probably one of the most studied and famous problem in graph algorithms. Exact methods fail to solve instances with more than few hundred vertices, therefore, a l…
cs.AI2024
Mixture of Public and Private Distributions in Imperfect Information Games
Jérôme Arjonilla, Abdallah Saffidine, Tristan Cazenave
In imperfect information games (e.g. Bridge, Skat, Poker), one of the fundamental considerations is to infer the missing information while at the same time avoiding the disclosure…