Bisimulation through probabilistic testing
Information and Computation
Bisimulation for probabilistic transition systems: a coalgebraic approach
Theoretical Computer Science
Bisimulation for labelled Markov processes
Information and Computation - Special issue: LICS'97
Approximating labelled Markov processes
Information and Computation
Towards a quantum programming language
Mathematical Structures in Computer Science
A hierarchy of probabilistic system types
Theoretical Computer Science - Selected papers of CMCS'03
An approximation algorithm for labelled Markov processes: towards realistic approximation
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Bisimulation and cocongruence for probabilistic systems
Information and Computation - Special issue: Seventh workshop on coalgebraic methods in computer science 2004
Stochastic transition systems for continuous state spaces and non-determinism
FOSSACS'05 Proceedings of the 8th international conference on Foundations of Software Science and Computation Structures
Continuous capacities on continuous state spaces
ICALP'07 Proceedings of the 34th international conference on Automata, Languages and Programming
A logical duality for underspecified probabilistic systems
Information and Computation
Measurable stochastics for Brane Calculus
Theoretical Computer Science
Approximating Markov processes through filtration
Theoretical Computer Science
Dexter kozen's influence on the theory of labelled markov processes
Logic and Program Semantics
Approximating Bisimilarity for Markov Processes
Electronic Notes in Theoretical Computer Science (ENTCS)
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We take a dual view of Markov processes --- advocated by Kozen --- as transformers of bounded measurable functions. 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 approximation. (iii) It is possible to show that there is a minimal bisimulation equivalent to a process obtained as the limit of the finite approximants.