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[P] RLCard: A Toolkit for Reinforcement Learning in Card Games

Hi,

We’ve recently worked on imperfect information games and reinforcement learning, and we would like to share our toolkit to everyone. RLCard supports various popular card games such as UNO, blackjack, Leduc Hold’em and Texas Hold’em. It also has some examples of basic reinforcement learning algorithms, such as Deep Q-learning, Neural Fictitious Self-Play (NFSP) and Counter Factual Regret Minimization (CFR). Also, it has a simple interface to play with the pre-trained agent. Any generous comments will be appreciated. Have fun!

Github: https://github.com/datamllab/rlcard

submitted by /u/lhenry15
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.