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This paper proposes a study of the resilience and efficiency of automaticallygenerated industrial automation and control systems using Large Language Models(LLMs). The approach involves modeling the system using percolation theory toestimate its resilience and formulating the design problem as an optimizationproblem subject to constraints. Techniques from stochastic optimization andregret analysis are used to find a near-optimal solution with provable regretbounds. The study aims to provide insights into the effectiveness andreliability of automatically generated systems in industrial automation andcontrol, and to identify potential areas for improvement in their design andimplementation.

Resiliency Analysis of LLM generated models for Industrial Automation