RLCard is a toolkit for reinforcement learning research on card games. It includes several popular card games and focuses on learning algorithms for imperfect information games like poker and blackjack.

Features

  • Provides a suite of card game environments for RL training
  • Includes implementations of Texas Hold’em, Blackjack, and others
  • Focuses on imperfect information and multi-agent learning
  • Compatible with Gym-like APIs for easy integration
  • Supports opponent modeling and strategy learning
  • Includes benchmark models for performance comparison

Project Samples

Project Activity

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License

MIT License

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RLCard Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Reinforcement Learning Libraries

Registered

2025-03-13