Pokemon Showdown AI (ELO 1900+)
I’ve spent some time recently building an RL agent to play competitive Pokémon (Generation 9 Random Battles on Pokémon Showdown). I wanted to share the architecture, the training pipeline, and some thoughts on the MCTS vs. pure-network approaches in this specific environment. Why Pokémon? From an RL perspective, a Pokémon battle is a great proxy for real-world, messy decision-making. It combines three massive headaches: Simultaneous Action: Both agents lock in actions concurrently. You are trying to approximate Nash […]