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Probabilistic Cluster Unfoldings for Petri Nets

Stefan Haar 1
1 SIGMA2 - Signal, models, algorithms
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : This article introduces a probabilistic unfolding semantics for untimed Petri nets. No structural or safety assumptions are made. We show that cluster semantics is an adequate framework for the construction of probability measures for concurrent runs. The unfolding semantics is constructed by local choices on each cluster, and a distributed scheduling mechanism (cluster net) authorizing cluster actions. The probability measures for the choice of step in a cluster are obtained by constructing Markov Fields on the conflict graph of transitions, from suitable Gibbs potentials. We introduce and characterize stopping times for these models, and a strong Markov property.
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https://hal.inria.fr/inria-00072162
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Submitted on : Tuesday, May 23, 2006 - 7:56:50 PM
Last modification on : Thursday, February 11, 2021 - 2:48:05 PM
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  • HAL Id : inria-00072162, version 1

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Stefan Haar. Probabilistic Cluster Unfoldings for Petri Nets. [Research Report] RR-4426, INRIA. 2002. ⟨inria-00072162⟩

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