Skip to Main content Skip to Navigation
Journal articles

Probabilistic Cluster Unfoldings

Stefan Haar 1 
1 SIGMA2 - Signal, models, algorithms
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : This article introduces probabilistic cluster branching processes, a probabilistic unfolding semantics for untimed Petri nets, with no structural or safety assumptions, giving probability measures for concurrent runs. The unfolding is constructed by local choices on each cluster (conflict closed subnet), while the authorization for cluster actions is governed by a stochastic trace, the policy, that authorizes cluster actions. We introduce and characterize stopping times for these models, and prove a strong Markov property. Particularly adaquate probability measures for the choice of step in a cluster, as well as for the policy, are obtained by constructing Markov Fields from suitable marking-dependent Gibbs potentials.
Document type :
Journal articles
Complete list of metadata

https://hal.inria.fr/inria-00638276
Contributor : Stefan Haar Connect in order to contact the contributor
Submitted on : Friday, November 4, 2011 - 2:36:17 PM
Last modification on : Friday, February 4, 2022 - 3:18:58 AM

Identifiers

  • HAL Id : inria-00638276, version 1

Citation

Stefan Haar. Probabilistic Cluster Unfoldings. Fundamenta Informaticae, Polskie Towarzystwo Matematyczne, 2002, 53 (3-4), pp.281-314. ⟨inria-00638276⟩

Share

Metrics

Record views

30