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

Author

Chen, Xi ; Ching, Wai-Ki

Author_Institution

Dept. of Math., Univ. of Hong Kong, Hong Kong, China

fYear

2011

fDate

2-4 Sept. 2011

Firstpage

274

Lastpage

278

Abstract

In 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.

Keywords

Boolean functions; bioinformatics; biological techniques; biomedical engineering; cellular biophysics; complex networks; dynamic programming; genetics; medical computing; molecular biophysics; probability; PBN; dynamic programming; gene regulatory network; optimal control policy; probabilistic Boolean networks; state reduction approach; Boolean functions; Complexity theory; Conferences; Dynamic programming; Heuristic algorithms; Optimal control; Probabilistic logic;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Biology (ISB), 2011 IEEE International Conference on

Conference_Location

Zhuhai

Print_ISBN

978-1-4577-1661-4

Electronic_ISBN

978-1-4577-1665-2

Type

conf

DOI

10.1109/ISB.2011.6033165

Filename

6033165