mlsanityData to 14 Oct 2026

Abstraction-based Probabilistic Stability Analysis of Polyhedral Probabilistic Hybrid Systems

arXiv 2304.02647 ↗First posted 29 Mar 2023cs.AI cs.SY eess.SYcited by 0

Not on the map. Why?

Abstract (arXiv)

In this paper, we consider the problem of probabilistic stability analysis of a subclass of Stochastic Hybrid Systems, namely, Polyhedral Probabilistic Hybrid Systems (PPHS), where the flow dynamics is given by a polyhedral inclusion, the discrete switching between modes happens probabilistically at the boundaries of their invariant regions and the continuous state is not reset during switching. We present an abstraction-based analysis framework that consists of constructing a finite Markov Decision Processes (MDP) such that verification of certain property on the finite MDP ensures the satisfaction of probabilistic stability on the PPHS. Further, we present a polynomial-time algorithm for verifying the corresponding property on the MDP. Our experimental analysis demonstrates the feasibility of the approach in successfully verifying probabilistic stability on PPHS of various dimensions and sizes.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 36 references that are in the map. First posted on arXiv 29 Mar 2023.

Builds on

3 of 36 references.

References · 3

  1. 2013Faster Algorithms for Markov Decision Processes with Low Treewidthcited by 2
  2. 2017Efficient Strategy Iteration for Mean Payoff in Markov Decision Processescited by 2
  3. 2021Stability Analysis of Planar Probabilistic Piecewise Constant Derivative Systemscited by 1

Built on by

Not cited yet.