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Fighting wildfires under uncertainty - a sequential resource allocation approach
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Chan, Hau, Tran-Thanh, Long and Viswanathan, Vignesh (2020) Fighting wildfires under uncertainty - a sequential resource allocation approach. In: Twenty-Ninth International Joint Conference on Artificial Intelligence, Jan 2021. Published in: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence pp. 4322-4329. ISBN 9780999241165. doi:10.24963/ijcai.2020/596
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Official URL: http://dx.doi.org/10.24963/ijcai.2020/596
Abstract
Standard disaster response involves using drones (or helicopters) for reconnaissance and using people on the ground to mitigate the damage. In this paper, we look at the problem of wildfires and propose an efficient resource allocation strategy to cope with both dynamically changing environment and uncertainty. In particular, we propose Firefly, a new resource allocation algorithm, that can provably achieve optimal or near optimal solutions with high probability by first efficiently allocating observation drones to collect information to reduce uncertainty, and then allocate the firefighting units to extinguish fire. For the former, Firefly uses a combination of maximum set coverage formulation and a novel utility estimation technique, and it uses a knapsack formulation to calculate the allocation for the latter. We also demonstrate empirically by using a real-world dataset that Firefly achieves up to 80-90% performance of the offline optimal solution, even with a small amount of drones, in most of the cases.
Item Type: | Conference Item (Paper) | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Journal or Publication Title: | Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence | ||||||
Publisher: | International Joint Conferences on Artificial Intelligence | ||||||
ISBN: | 9780999241165 | ||||||
Book Title: | Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence | ||||||
Official Date: | July 2020 | ||||||
Dates: |
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Page Range: | pp. 4322-4329 | ||||||
DOI: | 10.24963/ijcai.2020/596 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 23 July 2020 | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | Twenty-Ninth International Joint Conference on Artificial Intelligence | ||||||
Type of Event: | Conference | ||||||
Date(s) of Event: | Jan 2021 | ||||||
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