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Multiagent MST Cover: Pleasing All Optimally via a Simple Voting Rule
Li, Bo1; Wu, Xiaowei2; Xu, Chenyang3,4; Zhang, Ruilong5
2023-06-27
Conference Name37th AAAI Conference on Artificial Intelligence, AAAI 2023
Source PublicationProceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
Volume37
Pages5730-5738
Conference Date7 February 2023through 14 February 2023
Conference PlaceWashington
PublisherAAAI Press
Abstract

Given a connected graph on whose edges we can build roads to connect the nodes, a number of agents hold possibly different perspectives on which edges should be selected by assigning different edge weights. Our task is to build a minimum number of roads so that every agent has a spanning tree in the built subgraph whose weight is the same as a minimum spanning tree in the original graph. We first show that this problem is NP-hard and does not admit better than ((1 - o(1)) ln k)approximation polynomial-time algorithms unless P = NP, where k is the number of agents. We then give a simple voting algorithm with an optimal approximation ratio. Moreover, our algorithm only needs to access the agents' rankings on the edges. Finally, we extend our results to submodular objective functions and Matroid rank constraints.

URLView the original
Language英語English
Scopus ID2-s2.0-85167869632
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Document TypeConference paper
CollectionTHE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Affiliation1.Department of Computing, The Hong Kong Polytechnic University, Hong Kong
2.IOTSC, University of Macau, Macao
3.Software Engineering Institute, East China Normal University, China
4.College of Computer Science, Zhejiang University, China
5.Department of Computer Science, City University of Hong Kong, Hong Kong
Recommended Citation
GB/T 7714
Li, Bo,Wu, Xiaowei,Xu, Chenyang,et al. Multiagent MST Cover: Pleasing All Optimally via a Simple Voting Rule[C]:AAAI Press, 2023, 5730-5738.
APA Li, Bo., Wu, Xiaowei., Xu, Chenyang., & Zhang, Ruilong (2023). Multiagent MST Cover: Pleasing All Optimally via a Simple Voting Rule. Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, 37, 5730-5738.
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