Results 1 
3 of
3
Continuous Stochastic Logic Characterizes Bisimulation of Continuoustime Markov Processes
 J. of Logic and Alg. Progr
, 2002
"... In a recent paper Baier, Haverkort, Hermanns and Katoen [BHHK00], analyzed a new way of modelchecking formulas of a logic for continuoustime processes  called Continuous Stochastic Logic (henceforth CSL) { against continuoustime Markov chains { henceforth CTMCs. One of the important results o ..."
Abstract

Cited by 15 (3 self)
 Add to MetaCart
In a recent paper Baier, Haverkort, Hermanns and Katoen [BHHK00], analyzed a new way of modelchecking formulas of a logic for continuoustime processes  called Continuous Stochastic Logic (henceforth CSL) { against continuoustime Markov chains { henceforth CTMCs. One of the important results of that paper was the proof that if two CTMCs were bisimilar then they would satisfy exactly the same formulas of CSL. This raises the converse question { does satisfaction of the same collection of CSL formulas imply bisimilarity? In other words, given two CTMCs which are known to satisfy exactly the same formulas of CSL does it have to be the case that they are bisimilar? We prove that the answer to the question just raised is \yes". In fact we prove a signi cant extension, namely that a subset of CSL suces even for systems where the statespace may be a continuum. Along the way we prove a result to the eect that the set of Zeno paths has measure zero provided that the transition rates are bounded.
Approximating Markov Processes By Averaging
"... Normally, one thinks of probabilistic transition systems as taking an initial probability distribution over the state space into a new probability distribution representing the system after a transition. We, however, take a dual view of Markov processes as transformers of bounded measurable function ..."
Abstract
 Add to MetaCart
Normally, one thinks of probabilistic transition systems as taking an initial probability distribution over the state space into a new probability distribution representing the system after a transition. We, however, take a dual view of Markov processes as transformers of bounded measurable functions. This is very much in the same spirit as a “predicatetransformer ” view, which is dual to the statetransformer view of transition systems. We redevelop the theory of labelled Markov processes from this view point, in particular we explore approximation theory. We obtain three main results: (i) It is possible to define bisimulation on general measure spaces and show that it is an equivalence relation. The logical characterization of bisimulation can be done straightforwardly and generally. (ii) A new and flexible approach to approximation based on averaging can be given. This vastly generalizes and streamlines the idea of using conditional expectations to compute approximations. (iii) We show that there is a minimal process bisimulationequivalent to a given process, and this minimal process is obtained as the limit of the finite approximants.