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

See All Activity >

License

MIT License

Follow RLCard

RLCard Web Site

Other Useful Business Software
Earn up to 16% annual interest with Nexo. Icon
Earn up to 16% annual interest with Nexo.

Let your crypto work for you

Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
Get started with Nexo.
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of RLCard!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Reinforcement Learning Libraries

Registered

2025-03-13