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cs.AI2026
Evaluating LLMs as Interpretable Controllers for Dynamical Systems
Aleksander Ãstensen, Alberto Mino Calero, Anastasios M. Lekkas +1
Large Language Models (LLMs) are increasingly used for decision-making and reasoning tasks, yet their potential as controllers for physical systems remains largely unexplored. This…
cs.AI2025
Hybrid Modeling, Sim-to-Real Reinforcement Learning, and Large Language Model Driven Control for Digital Twins
Adil Rasheed, Oscar Ravik, Omer San
This work investigates the use of digital twins for dynamical system modeling and control, integrating physics-based, data-driven, and hybrid approaches with both traditional and A…