Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network
The study of the multi-agent task allocation problem with multiple depots is crucial for investigating multi-agent collaboration. Although many traditional heuristic algorithms can be adopted to handle the concerned task allocation problem, they are not able to efficiently obtain optimal or suboptim...
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Format: | Article |
Language: | English |
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MDPI AG
2023-08-01
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Series: | Electronics |
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Online Access: | https://www.mdpi.com/2079-9292/12/16/3378 |
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author | Wen Shi Chengpu Yu |
author_facet | Wen Shi Chengpu Yu |
author_sort | Wen Shi |
collection | DOAJ |
description | The study of the multi-agent task allocation problem with multiple depots is crucial for investigating multi-agent collaboration. Although many traditional heuristic algorithms can be adopted to handle the concerned task allocation problem, they are not able to efficiently obtain optimal or suboptimal solutions. To this end, a graph attention pointer network is built in this paper to deal with the multi-agent task allocation problem. Specifically, the multi-head attention mechanism is employed for the feature extraction of nodes, and a pointer network with parallel two-way selection and parallel output is introduced to further improve the performance of multi-agent cooperation and the efficiency of task allocation. Experimental results are provided to show that the presented graph attention pointer network outperforms the traditional heuristic algorithms. |
first_indexed | 2024-03-10T23:59:21Z |
format | Article |
id | doaj.art-888e2aeb021843deadb10f091290d971 |
institution | Directory Open Access Journal |
issn | 2079-9292 |
language | English |
last_indexed | 2024-03-10T23:59:21Z |
publishDate | 2023-08-01 |
publisher | MDPI AG |
record_format | Article |
series | Electronics |
spelling | doaj.art-888e2aeb021843deadb10f091290d9712023-11-19T00:52:43ZengMDPI AGElectronics2079-92922023-08-011216337810.3390/electronics12163378Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer NetworkWen Shi0Chengpu Yu1School of Automation, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Automation, Beijing Institute of Technology, Beijing 100081, ChinaThe study of the multi-agent task allocation problem with multiple depots is crucial for investigating multi-agent collaboration. Although many traditional heuristic algorithms can be adopted to handle the concerned task allocation problem, they are not able to efficiently obtain optimal or suboptimal solutions. To this end, a graph attention pointer network is built in this paper to deal with the multi-agent task allocation problem. Specifically, the multi-head attention mechanism is employed for the feature extraction of nodes, and a pointer network with parallel two-way selection and parallel output is introduced to further improve the performance of multi-agent cooperation and the efficiency of task allocation. Experimental results are provided to show that the presented graph attention pointer network outperforms the traditional heuristic algorithms.https://www.mdpi.com/2079-9292/12/16/3378task allocationattention mechanismmulti-agent system |
spellingShingle | Wen Shi Chengpu Yu Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network Electronics task allocation attention mechanism multi-agent system |
title | Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network |
title_full | Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network |
title_fullStr | Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network |
title_full_unstemmed | Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network |
title_short | Multi-Agent Task Allocation with Multiple Depots Using Graph Attention Pointer Network |
title_sort | multi agent task allocation with multiple depots using graph attention pointer network |
topic | task allocation attention mechanism multi-agent system |
url | https://www.mdpi.com/2079-9292/12/16/3378 |
work_keys_str_mv | AT wenshi multiagenttaskallocationwithmultipledepotsusinggraphattentionpointernetwork AT chengpuyu multiagenttaskallocationwithmultipledepotsusinggraphattentionpointernetwork |