Mutual Information Optimal Control of Discrete-Time Linear Systems
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908447078875136 |
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| author | Enami, Shoju Kashima, Kenji |
| author_facet | Enami, Shoju Kashima, Kenji |
| contents | In this paper, we formulate a mutual information optimal control problem (MIOCP) for discrete-time linear systems. This problem can be regarded as an extension of a maximum entropy optimal control problem (MEOCP). Differently from the MEOCP where the prior is fixed to the uniform distribution, the MIOCP optimizes the policy and prior simultaneously. As analytical results, under the policy and prior classes consisting of Gaussian distributions, we derive the optimal policy and prior of the MIOCP with the prior and policy fixed, respectively. Using the results, we propose an alternating minimization algorithm for the MIOCP. Through numerical experiments, we discuss how our proposed algorithm works. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04712 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mutual Information Optimal Control of Discrete-Time Linear Systems Enami, Shoju Kashima, Kenji Optimization and Control Machine Learning Systems and Control In this paper, we formulate a mutual information optimal control problem (MIOCP) for discrete-time linear systems. This problem can be regarded as an extension of a maximum entropy optimal control problem (MEOCP). Differently from the MEOCP where the prior is fixed to the uniform distribution, the MIOCP optimizes the policy and prior simultaneously. As analytical results, under the policy and prior classes consisting of Gaussian distributions, we derive the optimal policy and prior of the MIOCP with the prior and policy fixed, respectively. Using the results, we propose an alternating minimization algorithm for the MIOCP. Through numerical experiments, we discuss how our proposed algorithm works. |
| title | Mutual Information Optimal Control of Discrete-Time Linear Systems |
| topic | Optimization and Control Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2507.04712 |