Reinforcement Learning for the Game of Balatro: A Fast Simulator and Two-Policy Training Approach
Balatro, a 2024 roguelike deckbuilder, presents three difficulties that have historically derailed reinforcement learning methods: a 3,000-action state-dependent action space, horizons of several hundred decisions with sparse rewards, and pervasive stochasticity in both card draws and shop generation. Published RL resu...
Ajay Vikram Periasami, Anjaneya Gupta, Ethan Cheng et al.
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