datamllab/rlcard
Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
This toolkit helps researchers and game AI developers create and test AI bots for popular card games like Poker, Blackjack, and Mahjong. You can input various reinforcement learning algorithms and game parameters to train AI agents, and the output is a high-performing bot that can play the specified card game. It's designed for anyone working on artificial intelligence for imperfect information games.
3,416 stars. Used by 1 other package. No commits in the last 6 months. Available on PyPI.
Use this if you are developing or studying advanced AI strategies for card games and need a robust, pre-built environment for training and evaluating your agents.
Not ideal if you are looking for a simple, ready-to-play AI opponent without wanting to delve into algorithm development.
Stars
3,416
Forks
732
Language
Python
License
MIT
Category
Last pushed
Jun 26, 2024
Commits (30d)
0
Reverse dependents
1
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/agents/datamllab/rlcard"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related agents
Toni-SM/skrl
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with...
facebookresearch/BenchMARL
BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL...
utiasDSL/gym-pybullet-drones
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
gtri/scrimmage
Multi-Agent Robotics Simulator
proroklab/VectorizedMultiAgentSimulator
VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement...