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Conference Paper: Finding optimal control policy by using dynamic programming in conjunction with state reduction

TitleFinding optimal control policy by using dynamic programming in conjunction with state reduction
Authors
Chen, XChing, WK
KeywordsComputational costs
Large networks
Numerical example
Optimal control policy
Probabilistic boolean networks
Issue Date2011
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800515
Citation
The 2011 IEEE International Conference on Systems Biology (ISB), Zhuhai, China, 2-4 September 2011. In Proceedings of ISB, 2011, p. 274-278 How to Cite?
DOI: http://dx.doi.org/10.1109/ISB.2011.6033165
AbstractIn this paper we study the problem of finding optimal control policy for probabilistic Boolean networks (PBNs). Previous works have been done by using dynamic programming-based (DP) method. However, due to the high computational complexity of PBNs, DP method is computationally inefficient for large networks. Inspired by the state reduction strategies studied in [10], we consider using dynamic programming in conjunction with state reduction approach to reduce the computational cost of DP method. Numerical examples are given to demonstrate the efficiency of our proposed method. © 2011 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/140310
ISBN
978-1-4577-1666-9
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorChen, Xen_HK
dc.contributor.authorChing, WKen_HK
dc.date.accessioned2011-09-23T06:10:09Z-
dc.date.available2011-09-23T06:10:09Z-
dc.date.issued2011en_HK
dc.identifier.citationThe 2011 IEEE International Conference on Systems Biology (ISB), Zhuhai, China, 2-4 September 2011. In Proceedings of ISB, 2011, p. 274-278en_HK
dc.identifier.isbn978-1-4577-1666-9-
dc.identifier.urihttp://hdl.handle.net/10722/140310-
dc.description.abstractIn this paper we study the problem of finding optimal control policy for probabilistic Boolean networks (PBNs). Previous works have been done by using dynamic programming-based (DP) method. However, due to the high computational complexity of PBNs, DP method is computationally inefficient for large networks. Inspired by the state reduction strategies studied in [10], we consider using dynamic programming in conjunction with state reduction approach to reduce the computational cost of DP method. Numerical examples are given to demonstrate the efficiency of our proposed method. © 2011 IEEE.en_HK
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800515en_US
dc.relation.ispartofProceedings of the IEEE International Conference on Systems Biology, ISB 2011en_HK
dc.subjectComputational costs-
dc.subjectLarge networks-
dc.subjectNumerical example-
dc.subjectOptimal control policy-
dc.subjectProbabilistic boolean networks-
dc.titleFinding optimal control policy by using dynamic programming in conjunction with state reductionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=978-1-4577-1666-9&volume=&spage=274&epage=278&date=2011&atitle=Finding+optimal+control+policy+by+using+dynamic+programming+in+conjunction+with+state+reduction-
dc.identifier.emailChing, WK:wching@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ISB.2011.6033165en_HK
dc.identifier.scopuseid_2-s2.0-80054863882en_HK
dc.identifier.hkuros195883en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80054863882&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage274en_HK
dc.identifier.epage278en_HK
dc.description.otherThe 2011 IEEE International Conference on Systems Biology (ISB), Zhuhai, China, 2-4 September 2011. In Proceedings of ISB, 2011, p. 274-278-
dc.identifier.scopusauthoridChen, X=24334384300en_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK

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