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AI-Driven Decision-Making for Water Resources Planning and Hazard Mitigation Using Automated Multi Agents
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Abstract
This project simulates the Multi-Hazard Tournament (MHT) framework, a decision support
system designed for the U.S. Army Corps of Engineers, using AI agents to enhance decisionmaking processes for flood mitigation and water resource management. The objective of the framework is to develop optimal strategies for protecting water resources, habitats, and
communities within a defined budget. The simulation integrates AutoGen for managing multiagent interactions and DarkIdol-Llama-3.1-8B, an advanced language model, to facilitate
complex, long-context discussions. AI agents are configured with distinct roles and engage in
structured dialogues to collaboratively evaluate and refine mitigation strategies. The study
demonstrates the potential of AI-driven simulations to replicate real-world collaborative
environments, improving stakeholder engagement and enhancing the efficiency of hazard
mitigation planning. The findings highlight the effectiveness of AI agents in multi-stakeholder
decision-making processes, offering valuable insights for disaster risk reduction and showcasing the benefits of integrating advanced technologies in planning. This work contributes significantly to fostering more resilient, well-prepared communities through innovative approaches to decision-making.
DOI
https://doi.org/10.31223/X5ZQ57
Subjects
Civil Engineering, Computational Engineering, Computer and Systems Architecture, Computer Engineering, Ecology and Evolutionary Biology, Education, Engineering, Environmental Engineering, Geotechnical Engineering, Higher Education, Hydraulic Engineering, Operations Research, Systems Engineering and Industrial Engineering, Risk Analysis, Scholarship of Teaching and Learning, Systems Engineering, Terrestrial and Aquatic Ecology, Transportation Engineering
Keywords
water resources planning, Hazard Mitigation, AI-Driven Agents, Multi-Agent System, Decision-Making, Budget Optimization., Hazard Mitigation, AI-Driven Agents, Multi-Agent System, decision-making, Budget Optimization
Dates
Published: 2024-12-27 06:35
Last Updated: 2024-12-27 14:35
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data Availability (Reason not available):
Data is shared in the paper.
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