Hierarchical Planning for Resource Allocation in Emergency Response Systems

• URL: http://arxiv.org/abs/2012.13300v2
• Date: Thu, 4 Mar 2021 03:17:15 GMT
• Title: Hierarchical Planning for Resource Allocation in Emergency Response Systems
• Authors: Geoffrey Pettet and Ayan Mukhopadhyay and Mykel Kochenderfer and Abhishek Dubey
• Abstract summary: A classical problem in city-scale cyber-physical systems is resource allocation under uncertainty. Online, offline, and decentralized approaches have been applied to such problems, but they have difficulty scaling to large decision problems. We present a general approach to hierarchical planning that leverages structure in city-level CPS problems for resource allocation under uncertainty.
• Score: 0.8602553195689513
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: A classical problem in city-scale cyber-physical systems (CPS) is resource allocation under uncertainty. Typically, such problems are modeled as Markov (or semi-Markov) decision processes. While online, offline, and decentralized approaches have been applied to such problems, they have difficulty scaling to large decision problems. We present a general approach to hierarchical planning that leverages structure in city-level CPS problems for resource allocation under uncertainty. We use the emergency response as a case study and show how a large resource allocation problem can be split into smaller problems. We then create a principled framework for solving the smaller problems and tackling the interaction between them. Finally, we use real-world data from Nashville, Tennessee, a major metropolitan area in the United States, to validate our approach. Our experiments show that the proposed approach outperforms state-of-the-art approaches used in the field of emergency response.

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