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This paper presents EntropyRuntime, a discrete-time control system for single and multi-agent LLM-driven and robotic agents that uses five execution gears with utility-gated dispatch and event-driven fallback to ensure safety, stability, and continuity. It provides formal proofs and evaluates on a three-agent UR5 robotic assembly cell, achieving 99.6% anomaly detection rate.
This paper presents a Product-Aware Autoencoder for robust anomaly detection in multi-product cyber-physical systems, addressing the blind spot of global models. It demonstrates improved detection accuracy over baseline in stress tests.