The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space
MetadataShow full item record
We consider autonomous partially observable Markov decision processes where the control action influences the observation process only. Considering entropy as the cost incurred by the Markov information state process, the optimal observability problem is posed as a Markov decision scheduling problem that minimizes the infinite horizon cost. This scheduling problem is shown to be equivalent to minimization of an entropy measure, called estimation entropy which is related to the invariant measure of the information state.
Showing items related by title, author, creator and subject.
Xia, Jianhong (Cecilia); Zeephongsekul, P. (2009)Tourist movement is a complex process, but it provides very useful information for park managers and tourist operators. This paper aims to establish a sound methodology for modelling the spatial and temporal movement of ...
Duong, Thi V. T. (2008)Modeling patterns in temporal data has arisen as an important problem in engineering and science. This has led to the popularity of several dynamic models, in particular the renowned hidden Markov model (HMM) [Rabiner, ...
Xia, Jianhong (Cecilia); Zeephongsekul, P.; Packer, D. (2010)Tourist movement is a complex process. It can be modelled from a number of different perspectives; for example, Tourism, Geography, Economics, Mathematics, Computer Sciences and Psychology. This paper aims to establish a ...