Agent Played Pokémon for 1,000 Turns. It Never Left the Bedroom
Blog post from Paper Compute Company
The author shares their journey of developing an autonomous Pokémon Red agent, starting with a simplistic strategy of completing game objectives quickly, similar to their childhood gaming approach. Initially, the agent struggled with basic navigation, getting stuck due to an incorrect memory address and lacking pathfinding capabilities, which led to repetitive and ineffective actions. Through extensive debugging, including setting up a virtual machine environment and utilizing telemetry tools, the author identified and rectified these issues by implementing a collision map, A* pathfinding, and session recording for better analysis. This process highlighted the importance of visibility into silent failures that appear as progress. The agent's evolution was accelerated by leveraging PyBoy's headless mode for faster emulation and an evolutionary framework inspired by AlphaEvolve, allowing it to improve performance over time. The project is published as open-source, encouraging others to refine the agent's strategy across different tiers. The experience underscored the significance of comprehensive logging and self-evaluation to prevent and correct errors, with the author's future goal being the creation of a fully autonomous system capable of self-assessment and improvement without human intervention.
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