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A research framework for fast prototyping of reinforcement learning algorithms, designed for easy experimentation and reproducibility.
A deep reinforcement learning library offering high-quality, single-file implementations of algorithms like PPO, DQN, and SAC for research and education.
A curated collection of Monte Carlo tree search research papers with implementations from top AI conferences.
Compile Java bytecode to native assembly for microcontrollers and retro platforms like Commodore 64, Sega Genesis, and Atari 2600.
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