lamer-meta-rl

Enable LLM agents to actively explore and adapt policies through meta-RL instead of converging to fixed behaviors. Uses cross-episode training with trajectory-level discounting and in-context policy adaptation via textual reflections—achieving 11-19% improvements in exploration-exploitation balance across interactive environments.

Independent GitHub snapshot · Automated classification · Original documentation governs