PowerDAG achieves 94-100% success on unseen distribution grid analysis queries by combining adaptive retrieval with similarity-decay cutoff and just-in-time supervision, outperforming ReAct, LangChain, and CrewAI baselines.
Powerchain: A verifiable agentic ai system for automating distribution grid analyses
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A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
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PowerDAG: Reliable Agentic AI System for Automating Distribution Grid Analysis
PowerDAG achieves 94-100% success on unseen distribution grid analysis queries by combining adaptive retrieval with similarity-decay cutoff and just-in-time supervision, outperforming ReAct, LangChain, and CrewAI baselines.
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Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.