arXiv Open Access 2025

Minimizing Control Attention:The Linear Gauss-Markov paradigm

Ralph Sabbagh Asmaa Eldesoukey Mahmoud Abdelgalil Tryphon T. Georgiou
Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

Penulis (4)

R

Ralph Sabbagh

A

Asmaa Eldesoukey

M

Mahmoud Abdelgalil

T

Tryphon T. Georgiou

Format Sitasi

Sabbagh, R., Eldesoukey, A., Abdelgalil, M., Georgiou, T.T. (2025). Minimizing Control Attention:The Linear Gauss-Markov paradigm. https://arxiv.org/abs/2512.07046

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Tahun Terbit
2025
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en
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arXiv
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