Towards Intelligent Emergency Management: A Scenario–Learning–Decision Framework Enabled by Large Language Models

To address the governance challenges of “delayed response, fragmented strategies, and cognitive disconnection” in traditional emergency management, this paper proposes an intelligent framework—Scenario–Learning–Decision (SLD)—powered by Large Language Models (LLMs). The framework integrates Multi-Agent Systems (MAS) and prospect theory-based parameter modeling to build an emergency simulation platform featuring scenario perception, human–AI learning, and collective decision-making. Using the 2022 wildfire in City C as a case study, the research verifies the effectiveness of the SLD model in complex emergency contexts and provides theoretical support and practical pathways for developing human-centered intelligent emergency decision-making systems.