datamllab/rlcard
RLCard is a reinforcement learning toolkit providing card game environments (poker, blackjack, Leduc, DouDizhu, Mahjong, UNO) with Gym-compatible interfaces for training AI game bots.
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The toolkit provides easy-to-use interfaces for implementing reinforcement learning and search algorithms in imperfect information games. It supports multiple card game environments compatible with OpenAI Gym, enabling training of AI agents that learn optimal strategies through self-play and other RL techniques. The project includes pre-trained agents and integrates with broader game AI resources.
Frequently asked
- What is datamllab/rlcard?
- RLCard is a reinforcement learning toolkit providing card game environments (poker, blackjack, Leduc, DouDizhu, Mahjong, UNO) with Gym-compatible interfaces for training AI game bots.
- Is rlcard open source?
- Yes — datamllab/rlcard is open source, released under the MIT license.
- What language is rlcard written in?
- datamllab/rlcard is primarily written in Python.
- How popular is rlcard?
- datamllab/rlcard has 3.5k stars on GitHub.
- Where can I find rlcard?
- datamllab/rlcard is on GitHub at https://github.com/datamllab/rlcard.