The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space
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...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
IEEE
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/24789 |
| _version_ | 1848751526935265280 |
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| author | Rezaeian, M. Vo, Ba-Ngu Evans, J. |
| author_facet | Rezaeian, M. Vo, Ba-Ngu Evans, J. |
| author_sort | Rezaeian, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T07:54:08Z |
| format | Journal Article |
| id | curtin-20.500.11937-24789 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:54:08Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-247892017-09-13T15:12:59Z The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space Rezaeian, M. Vo, Ba-Ngu Evans, J. observability Estimation entropy sensor scheduling partially observable Markov decision processes 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. 2010 Journal Article http://hdl.handle.net/20.500.11937/24789 10.1109/TAC.2010.2074231 IEEE restricted |
| spellingShingle | observability Estimation entropy sensor scheduling partially observable Markov decision processes Rezaeian, M. Vo, Ba-Ngu Evans, J. The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title | The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title_full | The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title_fullStr | The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title_full_unstemmed | The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title_short | The Optimal Observability of Partially Observable Markov Decision Processes: Discrete State Space |
| title_sort | optimal observability of partially observable markov decision processes: discrete state space |
| topic | observability Estimation entropy sensor scheduling partially observable Markov decision processes |
| url | http://hdl.handle.net/20.500.11937/24789 |