OpenLoopEvolve improves long-horizon agent performance by versioning and evolving the entire control loop as a policy asset, with online and offline modes that beat a fixed initial loop policy on YC-Bench.
Reflexion: Language agents with verbal reinforcement learning,
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OpenLoopEvolve: A Verifiable Self-Evolution Framework for Loop Policies in Long-Horizon Complex Tasks
OpenLoopEvolve improves long-horizon agent performance by versioning and evolving the entire control loop as a policy asset, with online and offline modes that beat a fixed initial loop policy on YC-Bench.