Game of Poker
5 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Game of Poker
Most implemented papers
RLCard: A Toolkit for Reinforcement Learning in Card Games
The goal of RLCard is to bridge reinforcement learning and imperfect information games, and push forward the research of reinforcement learning in domains with multiple agents, large state and action space, and sparse reward.
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
When applied to Leduc poker, Neural Fictitious Self-Play (NFSP) approached a Nash equilibrium, whereas common reinforcement learning methods diverged.
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker
Poker is the quintessential game of imperfect information, and a longstanding challenge problem in artificial intelligence.
Approximating Poker Probabilities with Deep Learning
Many poker systems, whether created with heuristics or machine learning, rely on the probability of winning as a key input.
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
Games are abstractions of the real world, where artificial agents learn to compete and cooperate with other agents.