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dc.contributor.author
Rolon, Maria de Los Milagros
dc.contributor.author
Martínez, Ernesto Carlos
dc.date.available
2019-02-14T18:16:29Z
dc.date.issued
2012-12
dc.identifier.citation
Rolon, Maria de Los Milagros; Martínez, Ernesto Carlos; Agent learning in autonomic manufacturing execution systems for enterprise networking; Pergamon-Elsevier Science Ltd; Computers & Industrial Engineering; 63; 4; 12-2012; 901-925
dc.identifier.issn
0360-8352
dc.identifier.uri
http://hdl.handle.net/11336/70200
dc.description.abstract
In enterprise networks, companies interact on a temporal basis through client-server relationships between order agents (clients) and resource agents (servers) acting as autonomic managers. In this work, the autonomic MES (@MES) proposed by Rolón and Martinez (2012) has been extended to allow selfish behavior and adaptive decision-making in distributed execution control and emergent scheduling. Agent learning in the @MES is addressed by rewarding order agents in order to continuously optimize their processing routes based on cost and reliability of alternative resource agents (servers). Service providers are rewarded so as to learn the quality level corresponding to each task which is used to define the processing time and cost for each client request. Two reinforcement learning algorithms have been implemented to simulate learning curves of client-server relationships in the @MES. Emerging behaviors obtained through generative simulation in a case study show that despite selfish behavior and policy adaptation in order and resource agents, the autonomic MES is able to reject significant disturbances and handle unplanned events successfully.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Agent-Based Simulation
dc.subject
Autonomic Systems
dc.subject
Distributed Production Control
dc.subject
Enterprise Networking
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Manufacturing Execution Systems
dc.subject
Multi-Agent Learning
dc.subject.classification
Ingeniería de Sistemas y Comunicaciones
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
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INGENIERÍAS Y TECNOLOGÍAS
dc.title
Agent learning in autonomic manufacturing execution systems for enterprise networking
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2019-02-12T17:23:10Z
dc.journal.volume
63
dc.journal.number
4
dc.journal.pagination
901-925
dc.journal.pais
Estados Unidos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Rolon, Maria de Los Milagros. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.description.fil
Fil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.journal.title
Computers & Industrial Engineering
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.cie.2012.06.004
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