Large-scale, dynamic and distributed coalition formation with spatial and temporal constraints
Large-scale, dynamic and distributed coalition formation with spatial and temporal constraints
The Coalition Formation with Spatial and Temporal constraints Problem (CFSTP) is a multi-agent task allocation problem in which few agents have to perform many tasks, each with its deadline and workload. To maximize the number of completed tasks, the agents need to cooperate by forming, disbanding and reforming coalitions. The original mathematical programming formulation of the CFSTP is difficult to implement, since it is lengthy and based on the problematic Big-M method. In this paper, we propose a compact and easy-to-implement formulation. Moreover, we design D-CTS, a distributed version of the state-of-the-art CFSTP algorithm. Using public London Fire Brigade records, we create a dataset with 347588 tasks and a test framework that simulates the mobilization of firefighters in dynamic environments. In problems with up to 150 agents and 3000 tasks, compared to DSA-SDP, a state-of-the-art distributed algorithm, D-CTS completes 3.79%±[42.22%,1.96%] more tasks, and is one order of magnitude more efficient in terms of communication overhead and time complexity. D-CTS sets the first large-scale, dynamic and distributed CFSTP benchmark.
108-125
Capezzuto, Luca
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Tarapore, Danesh
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Ramchurn, Sarvapali
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Capezzuto, Luca
c82f8041-e5c6-48f5-b264-aac2c18c07be
Tarapore, Danesh
fe8ec8ae-1fad-4726-abef-84b538542ee4
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Capezzuto, Luca, Tarapore, Danesh and Ramchurn, Sarvapali
(2021)
Large-scale, dynamic and distributed coalition formation with spatial and temporal constraints.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), .
(In Press)
Abstract
The Coalition Formation with Spatial and Temporal constraints Problem (CFSTP) is a multi-agent task allocation problem in which few agents have to perform many tasks, each with its deadline and workload. To maximize the number of completed tasks, the agents need to cooperate by forming, disbanding and reforming coalitions. The original mathematical programming formulation of the CFSTP is difficult to implement, since it is lengthy and based on the problematic Big-M method. In this paper, we propose a compact and easy-to-implement formulation. Moreover, we design D-CTS, a distributed version of the state-of-the-art CFSTP algorithm. Using public London Fire Brigade records, we create a dataset with 347588 tasks and a test framework that simulates the mobilization of firefighters in dynamic environments. In problems with up to 150 agents and 3000 tasks, compared to DSA-SDP, a state-of-the-art distributed algorithm, D-CTS completes 3.79%±[42.22%,1.96%] more tasks, and is one order of magnitude more efficient in terms of communication overhead and time complexity. D-CTS sets the first large-scale, dynamic and distributed CFSTP benchmark.
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Accepted/In Press date: 7 May 2021
Identifiers
Local EPrints ID: 452050
URI: http://eprints.soton.ac.uk/id/eprint/452050
ISSN: 0302-9743
PURE UUID: d2b2c30e-ebc2-4303-9161-0bb3d8b31e1f
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Date deposited: 09 Nov 2021 17:34
Last modified: 17 Mar 2024 03:46
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Contributors
Author:
Luca Capezzuto
Author:
Danesh Tarapore
Author:
Sarvapali Ramchurn
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