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강화학습기법의 동적일정계획에의 적용가능성에 대한 소고

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Author(s)
강장하
Issued Date
2017
Keyword
Flexible Manufacturing System Reinforcement Learning Dispatching Rules Dynamic Scheduling
Abstract
The ability to dynamically reschedule jobs is core of flexible manufacturing system. Reinforcement learning, a machine learning approach undergoing development in various control systems, offers advantages in dynamic environments. This paper presents a feasibility study on the reinforcement learning for a dynamic scheduling problem.
Alternative Title
Feasibility Study on the Reinforcement Learning for a Dynamic Scheduling Problem
Alternative Author(s)
Jangha Kang
Publisher
조선대학교 공학기술연구원
Citation
강장하. (2017). 강화학습기법의 동적일정계획에의 적용가능성에 대한 소고, 공학기술논문지 | Vol.10, No.4 p.453 ~ p.456
Type
Laboratory article
ISSN
2005-3142
URI
https://oak.chosun.ac.kr/handle/2020.oak/17626
http://www.chosun.ac.kr/user/indexSub.do?codyMenuSeq=23376167&siteId=riet&dum=dum&boardId=168878&page=10&command=view&boardSeq=255757&chkBoxSeq=&categoryId=&categoryDepth=&search=&column=null&searchDate1=&searchDate2=&selColumn=&myList=
Appears in Collections:
2017 > Vol.10, No.4
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