TY - GEN
T1 - Cooperative Multi-Agent Path Finding
T2 - 14th International Symposium on Combinatorial Search, SoCS 2021
AU - Greshler, Nir
AU - Gordon, Ofir
AU - Salzman, Oren
AU - Shimkin, Nahum
N1 - Publisher Copyright:
Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2021
Y1 - 2021
N2 - We introduce the Cooperative Multi-Agent Path Finding (Co-MAPF) problem, an extension to the classical MAPF problem, where cooperative behavior is incorporated. In this setting, a group of autonomous agents operate in a shared environment and have to complete cooperative tasks while avoiding collisions with the other agents in the group. This extension naturally models many real-world applications, where groups of agents are required to collaborate in order to complete a given task. To this end, we formalize the Co-MAPF problem and introduce Cooperative Conflict-Based Search (Co-CBS), a CBS-based algorithm for solving the problem optimally for a wide set of Co-MAPF problems. Co-CBS uses a cooperation-planning module integrated into CBS such that cooperation planning is decoupled from path planning. Finally, we present empirical results on several MAPF benchmarks demonstrating our algorithm’s properties.
AB - We introduce the Cooperative Multi-Agent Path Finding (Co-MAPF) problem, an extension to the classical MAPF problem, where cooperative behavior is incorporated. In this setting, a group of autonomous agents operate in a shared environment and have to complete cooperative tasks while avoiding collisions with the other agents in the group. This extension naturally models many real-world applications, where groups of agents are required to collaborate in order to complete a given task. To this end, we formalize the Co-MAPF problem and introduce Cooperative Conflict-Based Search (Co-CBS), a CBS-based algorithm for solving the problem optimally for a wide set of Co-MAPF problems. Co-CBS uses a cooperation-planning module integrated into CBS such that cooperation planning is decoupled from path planning. Finally, we present empirical results on several MAPF benchmarks demonstrating our algorithm’s properties.
UR - http://www.scopus.com/inward/record.url?scp=85118312784&partnerID=8YFLogxK
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AN - SCOPUS:85118312784
T3 - 14th International Symposium on Combinatorial Search, SoCS 2021
SP - 173
EP - 175
BT - 14th International Symposium on Combinatorial Search, SoCS 2021
A2 - Ma, Hang
A2 - Serina, Ivan
Y2 - 26 July 2021 through 30 July 2021
ER -