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Title: On Algorithmic Decision Procedures in Emergency Response Systems in Smart and Connected Communities
Emergency Response Management (ERM) is a critical problem faced by communities across the globe. Despite this, it is common for ERM systems to follow myopic decision policies in the real world. Principled approaches to aid ERM decision-making under uncertainty have been explored but have failed to be accepted into real systems. We identify a key issue impeding their adoption --- algorithmic approaches to emergency response focus on reactive, post-incident dispatching actions, i.e. optimally dispatching a responder after incidents occur. However, the critical nature of emergency response dictates that when an incident occurs, first responders always dispatch the closest available responder to the incident. We argue that the crucial period of planning for ERM systems is not post-incident, but between incidents. This is not a trivial planning problem --- a major challenge with dynamically balancing the spatial distribution of responders is the complexity of the problem. An orthogonal problem in ERM systems is planning under limited communication, which is particularly important in disaster scenarios that affect communication networks. We address both problems by proposing two partially decentralized multi-agent planning algorithms that utilize heuristics and exploit the structure of the dispatch problem. We evaluate our proposed approach using real-world data, and find that in several contexts, dynamic re-balancing the spatial distribution of emergency responders reduces both the average response time as well as its variance.  more » « less
Award ID(s):
1814958 1647015
NSF-PAR ID:
10175439
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
roceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems
Page Range / eLocation ID:
1046–1054
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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