Agent-MD: Selective LLM Intervention with Event-Driven Escalation for Stateful GCMC--MD Campaigns
Balancing LLM reasoning with deterministic rules for more reliable molecular simulation campaigns.
Long-running molecular simulation campaigns require repeated continuation from saved states, provenance-aware progression, adaptive assessment, and occasional interpretation of workflow conditions that cannot be resolved safely by fixed rules. Here, we present Agent-MD, a framewo...
ArXiv CS.AI
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Agent-MD demonstrates that scientific workflows benefit from a hybrid architecture that pairs deterministic rule-based systems with LLM oversight for complex, non-routine decision-making. This approach significantly enhances the reliability and auditability of long-running simulations by ensuring AI reasoning is applied only where it is strictly necessary.
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