DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, JM | ko |
dc.contributor.author | Lee, JayHyung | ko |
dc.date.accessioned | 2013-03-04T07:52:01Z | - |
dc.date.available | 2013-03-04T07:52:01Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2004-09 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS, v.2, no.3, pp.263 - 278 | - |
dc.identifier.issn | 1598-6446 | - |
dc.identifier.uri | http://hdl.handle.net/10203/82068 | - |
dc.description.abstract | This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques for dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed. | - |
dc.language | English | - |
dc.publisher | INST CONTROL AUTOMATION SYSTEMS ENGINEERS | - |
dc.title | Approximate dynamic programming strategies and their applicability for process control: A review and future directions | - |
dc.type | Article | - |
dc.identifier.wosid | 000226162300001 | - |
dc.identifier.scopusid | 2-s2.0-4544319442 | - |
dc.type.rims | ART | - |
dc.citation.volume | 2 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 263 | - |
dc.citation.endingpage | 278 | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | - |
dc.contributor.localauthor | Lee, JayHyung | - |
dc.contributor.nonIdAuthor | Lee, JM | - |
dc.type.journalArticle | Review | - |
dc.subject.keywordAuthor | approximate dynamic programming | - |
dc.subject.keywordAuthor | reinforcement learning | - |
dc.subject.keywordAuthor | neuro-dynamic programming | - |
dc.subject.keywordAuthor | optimal control | - |
dc.subject.keywordAuthor | function approximation | - |
dc.subject.keywordPlus | MODEL-PREDICTIVE CONTROL | - |
dc.subject.keywordPlus | NEURAL NETWORKS | - |
dc.subject.keywordPlus | TD-GAMMON | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | CONVERGENCE | - |
dc.subject.keywordPlus | ROBOTS | - |
dc.subject.keywordPlus | AGENTS | - |
dc.subject.keywordPlus | SPACES | - |
dc.subject.keywordPlus | STATE | - |
dc.subject.keywordPlus | TIME | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.