Information-Geometric First-Passage Monitoring of Distributional Stability in Stochastic Systems
Runtime monitoring of stochastic systems must distinguish nominal distributional relaxation from regime departure while controlling repeated-test false alarms under explicit validity assumptions. This paper links relative-entropy dissipation, information geometry, and sequential inference in a bounded first-passage monitoring architecture. For reversible Fokker--Planck dynamics, relative entropy to an invariant density is non-increasing; under exogenous forcing, its derivative decomposes into nominal dissipation and an information-space forcing term. The runtime layer uses Gaussian window surrogates, nominal-relative covariance shrinkage, a coordinate-consistent relative precision diagnos...
| Authors | Hikmat Karimov, Rahid Zahid Alekberli |
|---|---|
| Primary category | cs.AI |
| Published | 27 April 2026 |
| Last updated at source | 21 September 2026 |
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