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12 June 2023 Results of the airlift challenge: a multi-agent AI planning competition
Adis Delanovic, Carmen Chiu, John Kolen, Abeynaya Gnanasekaran, Amit Surana, Kunal Srivastava, Hongyu (Alice) Zhu, Yiqing Lin, Norman Bukingolts, Devin Willis, Nickolas Arustamyan, Adam Sardouk, Matthew Huynh, Dali Grimaux-De camps, Kaleb Smith, David Bragg, Andre Beckus
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Proceedings Volume 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V; 125381E (2023) https://doi.org/10.1117/12.2664868
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States
Abstract
Planning the delivery of cargo as part of an airlift operation is a notoriously complex problem. Transportation routes can suddenly become inaccessible due to poor weather or other unexpected occurrences. Factors such as airplane speed, carrying capacity, and airport maximum-on-ground must also be considered to ensure on-time and efficient delivery. Unforeseen cargo needs may require quick re-planning to meet tight deadlines. To address the problem, we held the Airlift Challenge, an online multi-agent planning competition which concluded in early 2023. Competitors in the Airlift Challenge created innovative algorithms to execute a simulated airlift operation. The algorithms were scored against a set of increasingly complex evaluation scenarios while contending with unexpected events and disruptions. In this paper, we describe the competition and simulation environment, summarize results, and include write-ups of the top approaches provided by the winning teams.
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Adis Delanovic, Carmen Chiu, John Kolen, Abeynaya Gnanasekaran, Amit Surana, Kunal Srivastava, Hongyu (Alice) Zhu, Yiqing Lin, Norman Bukingolts, Devin Willis, Nickolas Arustamyan, Adam Sardouk, Matthew Huynh, Dali Grimaux-De camps, Kaleb Smith, David Bragg, and Andre Beckus "Results of the airlift challenge: a multi-agent AI planning competition", Proc. SPIE 12538, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications V, 125381E (12 June 2023); https://doi.org/10.1117/12.2664868
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KEYWORDS
Machine learning
Evolutionary algorithms
Artificial intelligence
Mathematical optimization
Data modeling
Algorithm development
Decision making
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