Markov decision processes under observability constraints

Date

2005-06-01

Author

Serin, Yaşar Yasemin
Kulkarni, V

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We develop an algorithm to compute optimal policies for Markov decision processes subject to constraints that result from some observability restrictions on the process. We assume that the state of the Markov process is unobservable. There is an observable process related to the unobservable state. So, we want to find a decision rule depending only on this observable process. The objective is to minimize the expected average cost over an infinite horizon. We also analyze the possibility of performing observations in more detail to obtain improved policies.

Subject Keywords

Management Science and Operations Research, Software, General Mathematics

URI

https://hdl.handle.net/11511/48248

Collections

Department of Industrial Engineering, Article