datamllab/rlcard

Health v2 · maintenance only

Adoption not part of the score

3540 stars · 753 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

RLCard is a Python toolkit for reinforcement learning research in card games, providing environments for Blackjack, Leduc Hold'em, Texas Hold'em, Dou Dizhu, Mahjong, and UNO with easy-to-use interfaces for RL and search algorithms. It bridges reinforcement learning and imperfect-information games and supports PettingZoo multi-agent APIs.

Use cases

• train RL agents to play poker
• research imperfect information games
• benchmark reinforcement learning algorithms on card games
• build an AI bot for Dou Dizhu or Mahjong
• create a gym environment for a card game
• teach reinforcement learning with game examples

When to choose

• you need ready-made card game environments for RL experiments
• you want a Python library with PyTorch algorithm implementations
• you are studying multi-agent or imperfect-information game AI

When to avoid

• you need real-time or 3D game environments
• you want a production game bot service rather than a research toolkit
• you need perfect-information board games like chess or Go

Facets

library · maturity maintenance

reinforcement-learning simulation game-engine machine-learning reinforcement-learning artificial-intelligence machine-learning python cross-platform card-games poker imperfect-information-games gym-environment multi-agent game-ai blackjack doudizhu mahjong uno game-development

Member repositories

For agents

markdown · JSON · MCP: product_card(name="datamllab/rlcard")