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Home / Proceedings / Proceedings of the International Conference on Automated Planning and Scheduling, 30 / Book One

Algorithm Selection for Optimal Multi-Agent Pathfinding

February 1, 2023

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Authors

Omri Kaduri,Eli Boyarski,Roni Stern

Ben Gurion University of the Negev,Ben-Gurion University of the Negev,Ben Gurion University of the Negev


DOI:

10.1609/icaps.v30i1.6657


Abstract:

The challenge of finding an optimal solution to a multi-agent path finding (MAPF) problem has attracted significant academic and industrial interest in recent years. While the problem is NP-Hard, modern optimal MAPF algorithms can scale to solve problems with hundreds of agents. Nevertheless, no single optimal MAPF algorithm dominates all benchmarks problems, and there are no clear, provable, guidelines for when each algorithm should be used. To address this, we present the first successful Algorithm Selection (AS) model for optimal MAPF. We propose two approaches for learning an AS model. The first approach uses a standard supervised learning algorithm with a set of handcrafted MAPF-specific features. The second approach, casts a MAPF problem to an image and applies a deep Convolutional Neural Network to classify it. We evaluate both approaches over a large dataset and show that using an AS model to select which algorithm to use for each instance results in solving more problems and in a shorter runtime compared to the state of the art.

Topics: ICAPS

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HOW TO CITE:

Omri Kaduri,Eli Boyarski,Roni Stern Algorithm Selection for Optimal Multi-Agent Pathfinding Proceedings of the International Conference on Automated Planning and Scheduling, 30 (2020) 161-165.

Omri Kaduri,Eli Boyarski,Roni Stern Algorithm Selection for Optimal Multi-Agent Pathfinding ICAPS 2020, 161-165.

Omri Kaduri,Eli Boyarski,Roni Stern (2020). Algorithm Selection for Optimal Multi-Agent Pathfinding. Proceedings of the International Conference on Automated Planning and Scheduling, 30, 161-165.

Omri Kaduri,Eli Boyarski,Roni Stern. Algorithm Selection for Optimal Multi-Agent Pathfinding. Proceedings of the International Conference on Automated Planning and Scheduling, 30 2020 p.161-165.

Omri Kaduri,Eli Boyarski,Roni Stern. 2020. Algorithm Selection for Optimal Multi-Agent Pathfinding. "Proceedings of the International Conference on Automated Planning and Scheduling, 30". 161-165.

Omri Kaduri,Eli Boyarski,Roni Stern. (2020) "Algorithm Selection for Optimal Multi-Agent Pathfinding", Proceedings of the International Conference on Automated Planning and Scheduling, 30, p.161-165

Omri Kaduri,Eli Boyarski,Roni Stern, "Algorithm Selection for Optimal Multi-Agent Pathfinding", ICAPS, p.161-165, 2020.

Omri Kaduri,Eli Boyarski,Roni Stern. "Algorithm Selection for Optimal Multi-Agent Pathfinding". Proceedings of the International Conference on Automated Planning and Scheduling, 30, 2020, p.161-165.

Omri Kaduri,Eli Boyarski,Roni Stern. "Algorithm Selection for Optimal Multi-Agent Pathfinding". Proceedings of the International Conference on Automated Planning and Scheduling, 30, (2020): 161-165.

Omri Kaduri,Eli Boyarski,Roni Stern. Algorithm Selection for Optimal Multi-Agent Pathfinding. ICAPS[Internet]. 2020[cited 2023]; 161-165.


ISSN: 2334-0843


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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