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Intelligent Emergency Decision Support System Based on Multi-Agent Collaboration

• 1、 School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876

Abstract：To address the limitations of traditional emergency decision systems including single data sources, low intelligence levels, and rigid decision pathways, we propose an intelligent emergency decision support system based on multi-agent collaboration. The system employs a Plan-Execute-Monitor (PEM) cyclic architecture, integrating multi-source information fusion modules including Web search, knowledge graph querying, and geographic information services, and constructs a Tree-of-Thoughts-driven multi-agent collaboration mechanism. By introducing key techniques such as plan-oriented path generation, multi-dimensional progress evaluation, and adaptive execution monitoring, the system resolves critical issues in traditional multi-agent systems including instruction-following failures, step repetition, and context loss. We constructed a GAIA-Emergency Management domain dataset containing 135 tasks based on government open-source files and web crawling, referencing the GAIA evaluation framework. Experimental results on this dataset show that the PEM architecture achieves an accuracy of 48.7\%, outperforming the traditional iterative search architecture's 28.6\% by 20.1 percentage points, with an average execution time reduction of 63.7\%, validating the system's effectiveness.

Keywords： Emergency Decision-Making Multi-Agent System Large Language Model Tree of Thoughts LangGraph