LLM-Guided Contextual Action Evaluation for Operational Decisions in Industrial Processes

arXiv:2608.24156 · eess.SY, cs.AI, cs.ET, cs.SY · Submitted 2026-08-25 · Read on arXiv

eess.SY, cs.AI, cs.ET, cs.SY

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Actor — 26× in this paper · explained in 3 episodes
• Reinforcement Learning — 23× in this paper · explained in 4 episodes
• LLM-Guided Contextual Action Evaluation — 7× in this paper
• Deep Reinforcement Learning — 5× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Online Reinforcement Learning — 2× in this paper · explained in 2 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Digital Twin — 1× in this paper · explained in 5 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Knowledge graphs — 1× in this paper · explained in 2 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Continuous control with deep reinforcement learning
• LLM-Guided Task-Semantic Field Factorization for Industrial Process Forecasting
• Synthesizing Chemical Plant Operation Procedures using Knowledge, Dynamic Simulation and Deep Reinforcement Learning
• From Detection to Action: Using LLM Agents for Fault-Tolerant Control

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