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Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization · Stentor Studio

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Escher-Loop: Mutual Evolution by Closed-Loop Self-Referential Optimization

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abstract

While recent autonomous agents demonstrate impressive capabilities, they predominantly rely on manually scripted workflows and handcrafted heuristics, inherently limiting their potential for open-ended improvement. To address this, we propose Escher-Loop, a fully closed-loop framework that operationalizes the mutual evolution of two distinct populations: Task Agents that solve concrete problems, and Optimizer Agents…

Authors: Ziyang Liu, Xinyan Guo, Xuchen Wei, Han Hao, Liu Yang
Published: April 29, 2026
Duration: 7:33
arXiv: 2604.23472

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