Beating Pokemon Red with RL and <10M Parameters
Hi everyone! After spending hundreds of hours, we're excited to finally share our progress in developing a reinforcement learning system to beat Pokémon Red. Our system successfully completes the game using a policy under 10M parameters, PPO, and a few novel techniques. With the release of Claude Plays Pokémon, now feels like the perfect time to showcase our work. We'd love to get feedback!
In plain words
A reinforcement learning system that completes Pokémon Red using a policy under 10 million parameters and the PPO algorithm. The project demonstrates novel techniques for training game-playing AI agents on complex, turn-based RPGs. Designed for developers and AI enthusiasts interested in reinforcement learning applications, the work showcases how relatively compact neural networks can solve full-length video games through iterative training and optimization.
written from the facts on this page · September 2026
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