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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.07046 |
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| _version_ | 1866915659808505856 |
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| author | Sabbagh, Ralph Eldesoukey, Asmaa Abdelgalil, Mahmoud Georgiou, Tryphon T. |
| author_facet | Sabbagh, Ralph Eldesoukey, Asmaa Abdelgalil, Mahmoud Georgiou, Tryphon T. |
| contents | We revisit the concept of `attention' as a technical term to quantify the effort in calibrating control action based on available data. While Wiener, in his work on Cybernetics, anticipated key principles on prioritizing task-relevant signals, it was not until the late 1990's when Brockett first formulated pertinent optimization problems that have inspired subsequent as well as the present work. `Attention,' as a technical term, is defined so as to quantify the dependence of the control law on the time and space/state coordinate; a control law that is independent of time and space, assuming it meets specifications, requires vanishing attention. In the present work we focus on Linear-Markovian dynamics with Gaussian state uncertainty so as to analyze the structure of minimal-attention control schemes that steer the dynamics between terminal states with Gaussian uncertainty profile. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_07046 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Minimizing Control Attention:The Linear Gauss-Markov paradigm Sabbagh, Ralph Eldesoukey, Asmaa Abdelgalil, Mahmoud Georgiou, Tryphon T. Optimization and Control We revisit the concept of `attention' as a technical term to quantify the effort in calibrating control action based on available data. While Wiener, in his work on Cybernetics, anticipated key principles on prioritizing task-relevant signals, it was not until the late 1990's when Brockett first formulated pertinent optimization problems that have inspired subsequent as well as the present work. `Attention,' as a technical term, is defined so as to quantify the dependence of the control law on the time and space/state coordinate; a control law that is independent of time and space, assuming it meets specifications, requires vanishing attention. In the present work we focus on Linear-Markovian dynamics with Gaussian state uncertainty so as to analyze the structure of minimal-attention control schemes that steer the dynamics between terminal states with Gaussian uncertainty profile. |
| title | Minimizing Control Attention:The Linear Gauss-Markov paradigm |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2512.07046 |