Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
A new paper introduces a tool-augmented agent for closed-loop optimization, simulation, and modeling orchestration. This research explores advanced AI methodologies for improved system control and design. The paper, by Liyuan Deng and collaborators, delves into novel applications of AI.
A new research paper titled "Tool-Augmented Agent for Closed-loop Optimization, Simulation, and Modeling Orchestration" has been published by Liyuan Deng and eight other authors.
The paper is accessible in PDF format and explores advanced methodologies within artificial intelligence for improved system control and design. This work was submitted in April 2026.
Additional resources related to the paper, including bibliographic tools, citation tools, and links to code and data, are available through platforms like arXivLabs. These experimental projects allow collaborators to develop and share new features directly on the arXiv website.
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