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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.
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Submitted on : Friday, November 4, 2011 - 2:36:17 PM
Last modification on : Friday, February 4, 2022 - 3:18:58 AM


  • HAL Id : inria-00638276, version 1


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



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