AI RESEARCH
LLM-Driven Heuristic Synthesis for Industrial Process Control: Lessons from Hot Steel Rolling
arXiv CS.AI
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ArXi:2603.20537v1 Announce Type: new Industrial process control demands policies that are interpretable and auditable, requirements that black-box neural policies struggle to meet. We study an LLM-driven heuristic synthesis framework for hot steel rolling, in which a language model iteratively proposes and refines human-readable Python controllers using rich behavioral feedback from a physics-based simulator.