Interacting Particle System-based Estimation of Reach Probability for a Generalized Stochastic Hybrid System

Henk A.P. Blom, Hao Ma, G. J.(Bert) Bakker

Research output: Contribution to journalConference articleScientificpeer-review

2 Citations (Scopus)
45 Downloads (Pure)


This paper studies estimation of reach probability for a generalized stochastic hybrid system (GSHS). For diffusion processes a well-developed approach in reach probability estimation is to introduce a suitable factorization of the reach probability and then to estimate these factors through simulation of an Interacting Particle System (IPS). The theory of this IPS approach has been extended to arbitrary strong Markov processes, which includes GSHS executions. Because Monte Carlo simulation of GSHS particles involves sampling of Brownian motion as well as sampling of random discontinuities, the practical elaboration of the IPS approach for GSHS is not straightforward. The aim of this paper is to elaborate the IPS approach for GSHS by using complementary Monte Carlo sampling techniques. For a simple GSHS example, it is shown that and why the specific technique selected for sampling discontinuities can have a major influence on the effectiveness of IPS in reach probability estimation.

Original languageEnglish
Pages (from-to)79-84
Number of pages6
Issue number16
Publication statusPublished - 1 Jan 2018
EventADHS 2018: 6th IFAC Conference on Analysis and Design of Hybrid Systems - Oxford, United Kingdom
Duration: 11 Jul 201813 Jul 2018
Conference number: 6


  • Factorization
  • Interacting Particles
  • Rare event
  • Reach Probability
  • Stochastic Hybrid System


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