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Cooperative Multi-agent Systems for the Multi-target κ -Coverage Problem
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0001-7852-4582
DIGIT, Aarhus University, Aarhus, Denmark.
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1364-8127
2021 (Engelska)Ingår i: Lect. Notes Comput. Sci., Springer Science and Business Media Deutschland GmbH , 2021, s. 106-131Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

When multiple robots are required to collaborate in order to accomplish a specific task, they need to be coordinated in order to operate efficiently. To allow for scalability and robustness, we propose a novel distributed approach performed by autonomous robots based on their willingness to interact with each other. This willingness, based on their individual state, is used to inform a decision process of whether or not to interact with other robots within the environment. We study this new mechanism to form coalitions in the on-line multi-object κ -coverage problem, and evaluate its performance through two sets of experiments, in which we also compare to other methods from the state-of-art. In the first set we focus on scenarios with static and mobile targets, as well as with a different number of targets. Whereas in the second, we carry out an extensive analysis of the best performing methods focusing only on mobile targets, while also considering targets that appear and disappear during the course of the experiments. Results show that the proposed method is able to provide comparable performance to the best methods under study. 

Ort, förlag, år, upplaga, sidor
Springer Science and Business Media Deutschland GmbH , 2021. s. 106-131
Serie
Lecture Notes in Computer Science, ISSN 0302-9743 ; 12613 LNAI
Nyckelord [en]
Coalition formation, Collaborative agents, Coverage problem, Intelligent agents, Robots, Decision process, Distributed approaches, Mobile targets, Multi-targets, Multiple robot, New mechanisms, Specific tasks, Multi agent systems
Nationell ämneskategori
Data- och informationsvetenskap
Identifikatorer
URN: urn:nbn:se:mdh:diva-53892DOI: 10.1007/978-3-030-71158-0_5ISI: 000722435000005Scopus ID: 2-s2.0-85103477487ISBN: 9783030711573 (tryckt)OAI: oai:DiVA.org:mdh-53892DiVA, id: diva2:1544637
Konferens
12th International Conference on Agents and Artificial Intelligence, ICAART 2020; Valletta; Malta; 22 February 2020 through 24 February 2020
Tillgänglig från: 2021-04-15 Skapad: 2021-04-15 Senast uppdaterad: 2022-11-08Bibliografiskt granskad

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Frasheri, MirgitaPapadopoulos, Alessandro

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Totalt: 330 träffar
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