A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.
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Updated
Jan 16, 2024 - Python
A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.
Play Liar's Deck against game-theoretic agents — CFR heads-up, PSRO populations at 3-4 seats — with a spectate mode and a Learning panel
Multi-Agent RL Final Project (Grade 100, M.Sc. Data Science, HIT): PSRO built from scratch on Kuhn Poker — exploitability 0.0315 vs 1.25 for self-play under the same budget (39.7× lower), landing on Kuhn's analytic equilibrium family without being told
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