Reactive, Generative, and Stratified Models of Probabilistic Processes

   page       BibTeX_logo.png   
Rob J. Vanglabbeek, Scott A. Smolka, Bernhard Steffen
Information and Computation 121(1), pages 59-80

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.