AI & ML
Rate-Cost Tradeoffs in Nonlinear Control
arXiv math.IT0 views
arXiv:2604.20369v2 Announce Type: replace Abstract: We study finite-horizon rate-cost tradeoffs for general stochastic control systems, including nonlinear systems. Under an average control cost constraint, we show that the minimum expected communication rate lies within an additive logarithmic gap above the normalized directed information minimized over causal control policies. This establishes directed information as the operationally relevant quantity governing rate-limited control, extending its previously established roles in causal source coding and linear quadratic Gaussian (LQG) control to general nonlinear control systems.
Source:https://arxiv.org/abs/2604.20369PreviousThe Asymmetric Hamming Bidistance and Distributions over Binary Asymmetric ChannelsNextThe Closure of LCD-to-GI Reductions via Generalized Inner Products
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