Projects per year
Abstract
Multi-Agent Path Finding (MAPF) is the combinatorial problem of finding collision-free paths for multiple agents on a graph. This paper describes MAPF-based software for solving train planning and replanning problems on large-scale rail networks under uncertainty. The software recently won the 2020 Flatland Challenge, a NeurIPS competition trying to determine how to efficiently manage dense traffic on rail networks. The software incorporates many state-of-the-art MAPF or, in general, optimization technologies, such as prioritized planning, large neighborhood search, safe interval path planning, minimum communication policies, parallel computing, and simulated annealing. It can plan collision-free paths for thousands of trains within a few minutes and deliver deadlock-free actions in real-time during execution.
Original language | English |
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Title of host publication | Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling |
Editors | Susanne Biundo, Minh Do, Robert Goldman, Michael Katz, Qiang Yang, Hankz Hankui Zhuo |
Place of Publication | Palo Alto CA USA |
Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
Pages | 477-485 |
Number of pages | 9 |
ISBN (Electronic) | 9781713832317, 9781577358671 |
Publication status | Published - 2021 |
Event | International Conference on Automated Planning and Scheduling 2021 - Online, Guangzhou, China Duration: 2 Aug 2021 → 13 Aug 2021 Conference number: 31st https://ojs.aaai.org/index.php/ICAPS/issue/view/380 (Proceedings) |
Publication series
Name | Proceedings International Conference on Automated Planning and Scheduling, ICAPS |
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Publisher | Association for the Advancement of Artificial Intelligence (AAAI) |
Volume | 2021-August |
ISSN (Print) | 2334-0835 |
ISSN (Electronic) | 2334-0843 |
Conference
Conference | International Conference on Automated Planning and Scheduling 2021 |
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Abbreviated title | ICAPS 2021 |
Country/Territory | China |
City | Guangzhou |
Period | 2/08/21 → 13/08/21 |
Internet address |
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Projects
- 2 Finished
-
Improved Constraint Reasoning for Robust Multi-agent Path Planning
Stuckey, P., Harabor, D., Le Bodic, P., Gange, G. & Koenig, S.
1/01/20 → 31/12/24
Project: Research
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Personalised Public Transport
Harabor, D., Moser, I. & Ronald, N.
24/06/19 → 31/12/24
Project: Research