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Multiagent reinforcement learning methods to resolve demand capacity balance problems

Spatharis Christos, Kravaris Theocharis, Vouros, George A, Blekas Konstantinos D., Chalkiadakis Georgios, García José Manuel Cordero, Fernandez Esther Calvo

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URIhttp://purl.tuc.gr/dl/dias/491D12EE-D6EB-4D31-B04E-6A25CE948AD5-
Identifierhttps://doi.org/10.1145/3200947.3201010-
Identifierhttps://dl.acm.org/citation.cfm?id=3201010-
Languageen-
Extent9 pagesen
TitleMultiagent reinforcement learning methods to resolve demand capacity balance problemsen
CreatorSpatharis Christosen
CreatorKravaris Theocharisen
CreatorVouros, George Aen
CreatorBlekas Konstantinos D.en
CreatorChalkiadakis Georgiosen
CreatorΧαλκιαδακης Γεωργιοςel
CreatorGarcía José Manuel Corderoen
CreatorFernandez Esther Calvoen
PublisherAssociation for Computing Machineryen
Content SummaryIn this article, we explore the computation of joint policies for autonomous agents to resolve congestions problems in the air traffic management (ATM) domain. Agents, representing flights, have limited information about others’ payoffs and preferences, and need to coordinate to achieve their tasks while adhering to operational constraints. We formalize the problem as a multiagent Markov decision process (MDP) towards deciding flight delays to resolve demand and capacity balance (DCB) problems in ATM. To this end, we present multiagent reinforcement learning methods that allow agents to interact and form own policies in coordination with others. Experimental study on real-world cases, confirms the effectiveness of our approach in resolving the demand-capacity balance problem.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2019-08-30-
Date of Publication2018-
SubjectAir Traffic Managementen
SubjectCongestion problemsen
SubjectDemand Capacity Balanceen
SubjectMulti-agent reinforcement learningen
Bibliographic CitationC. Spatharis, T. Kravaris, G. A. Vouros, K. Blekas, G. Chalkiadakis, J.M.C. Garcia and E.C. Fernandez, "Multiagent reinforcement learning methods to resolve demand capacity balance problems," in 10th Hellenic Conference on Artificial Intelligence, 2018. doi: 10.1145/3200947.3201010en

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