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정무영

Jung, Mooyoung
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dc.citation.endPage 8743 -
dc.citation.number 10 -
dc.citation.startPage 8736 -
dc.citation.title EXPERT SYSTEMS WITH APPLICATIONS -
dc.citation.volume 39 -
dc.contributor.author Jung, Mooyoung -
dc.contributor.author Shin, Moonsoo -
dc.contributor.author Ryu, Kwangyeol -
dc.date.accessioned 2023-12-22T04:48:50Z -
dc.date.available 2023-12-22T04:48:50Z -
dc.date.created 2013-05-27 -
dc.date.issued 2012-08 -
dc.description.abstract Up-to-date market dynamics has been forcing manufacturing systems to adapt quickly and continuously to the ever-changing environment. Self-evolution of manufacturing systems means a continuous process of adapting to the environment on the basis of autonomous goal-formation and goal-oriented dynamic organization. This paper proposes a goal-regulation mechanism that applies a reinforcement learning approach, which is a principal working mechanism for autonomous goal-formation. Individual goals are regulated by a neural network-based fuzzy inference system, namely, a goal-regulation network (GRN) updated by a reinforcement signal from another neural network called goal-evaluation network (GEN). The GEN approximates the compatibility of goals with current environmental situation. In this paper, a production planning problem is also examined by a simulation study in order to validate the proposed goal regulation mechanism. -
dc.identifier.bibliographicCitation EXPERT SYSTEMS WITH APPLICATIONS, v.39, no.10, pp.8736 - 8743 -
dc.identifier.doi 10.1016/j.eswa.2012.01.207 -
dc.identifier.issn 0957-4174 -
dc.identifier.scopusid 2-s2.0-84859217892 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/2877 -
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84859217892 -
dc.identifier.wosid 000303281800024 -
dc.language 영어 -
dc.publisher PERGAMON-ELSEVIER SCIENCE LTD -
dc.title Reinforcement learning approach to goal-regulation in a self-evolutionary manufacturing system -
dc.type Article -
dc.relation.journalWebOfScienceCategory Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science -
dc.relation.journalResearchArea Computer Science; Engineering; Operations Research & Management Science -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Self-evolutionary manufacturing system -
dc.subject.keywordAuthor Fractal organization -
dc.subject.keywordAuthor Goal-regulation -
dc.subject.keywordAuthor Reinforcement learning -
dc.subject.keywordAuthor Agent -
dc.subject.keywordAuthor Production planning -

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