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RL agents can learn far more efficiently by dynamically distilling and leveraging past experiences that co-evolve with the agent's growing capabilities.
An open-source ecosystem for agentic learning, complete with a trained agent and novel policy optimization, promises to accelerate research by providing a standardized, scalable platform.