Dec 2025 - Present
Self-initiated project
Catan Learning Environment
An agent harness for LLM play in Settlers of Catan, built around a pure-Python engine and multi-agent training interface.
- Built a pure-Python game engine with a PettingZoo AEC wrapper, dual-channel observations, and an async player-trade state machine.
- Implemented a multimodal agent loop with persistent strategic memory, turn-trace state, and an event queue for opponent actions.
- Built a replay pipeline over 8.5K expert Colonist.io games, mapping Colonist coordinates into engine state and reconstructing observation-action pairs.