Reactive, Generative, and Stratified Models of Probabilistic Processes


Rob J. Vanglabbeek, Scott A. Smolka, Bernhard Steffen

We introduce three models of probabilistic processes, namely, reactive, generative, and stratified. These models are investigated within the context of PCCS, an extension of Milner's SCCS in which each summand of a process summation expression is guarded by a probability and the sum of these probabilities is 1. For each model, we present a structural operational semantics of PCCS and a notion of bisimulation equivalence which we prove to be a congruence. We also show that the models form a hierarchy: the reactive model is derivable from the generative model by abstraction from the relative probabilities of different actions, and the generative model is derivable from the stratified model by abstraction from the purely probabilistic branching structure. Moreover, the classical nonprobabilistic model is derivable from each of these models by abstraction from all probabilities.

Information and Computation 121(1), pages 59-80,  1995.

@article{probabilisticprocesses-inco121,
Author = {Vanglabbeek, Rob J. and Smolka, Scott A. and Steffen, Bernhard},
Doi = {10.1006/inco.1995.1123},
Issn = {0890-5401},
Journal = {Information and Computation},
Number = 1,
Pages = {59--80},
Title = {Reactive, Generative, and Stratified Models of Probabilistic Processes},
Url = {http://www.sciencedirect.com/science/article/pii/S0890540185711236},
Volume = 121,
Year = 1995}
Tags:

Publication

— authors

Rob J. Vanglabbeek, Scott A. Smolka, Bernhard Steffen

— status

published

— sort

article in journal

Venue

— journal

Information and Computation

— volume

121

— issue

1

— pages

59-80

— publication date

1995

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original page

Identifiers

— DOI

10.1006/inco.1995.1123

— print ISSN

0890-5401

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— BibTeX ID
probabilisticprocesses-inco121
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article

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