Scalable Implementation of Deep CFR and Single Deep CFR
-
Updated
May 6, 2020 - Python
Scalable Implementation of Deep CFR and Single Deep CFR
Omaha Poker functionality+some features for PokerRL Reinforcement Learning card framwork
Counterfactual regret minimization and Q-Learning for Blackjack and Hearts
Several agents that can play poker (using probability, monte carlo, etc.) and clustering to get the types of poker players.
Add a description, image, and links to the cfr topic page so that developers can more easily learn about it.
To associate your repository with the cfr topic, visit your repo's landing page and select "manage topics."