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Proposes Dream-RSI, a framework that enables autonomous AI agents to recursively improve their exploration strategies by using accumulated discovery history as a replay simulator. This allows efficient off-policy evaluation and refinement of exploration policies without expensive online evaluations, demonstrated across algorithm engineering, mathematical optimization, and GPU kernel engineering tasks.