Mathematical control theory: deterministic systems
Mathematical control theory: deterministic systems
Bisimulation through probabilistic testing
Information and Computation
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
The Metric Analogue of Weak Bisimulation for Probabilistic Processes
LICS '02 Proceedings of the 17th Annual IEEE Symposium on Logic in Computer Science
Bisimulation for Probabilistic Transition Systems: A Coalgebraic Approach
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
Probabilistic Simulations for Probabilistic Processes
CONCUR '94 Proceedings of the Concurrency Theory
Bisimulation for labelled Markov processes
Information and Computation - Special issue: LICS'97
Bisimulation for Labelled Markov Processes
LICS '97 Proceedings of the 12th Annual IEEE Symposium on Logic in Computer Science
Approximating labelled Markov processes
Information and Computation
Metrics for labelled Markov processes
Theoretical Computer Science - Logic, semantics and theory of programming
A hierarchy of probabilistic system types
Theoretical Computer Science - Selected papers of CMCS'03
Bisimulation and cocongruence for probabilistic systems
Information and Computation - Special issue: Seventh workshop on coalgebraic methods in computer science 2004
Measurable stochastics for Brane Calculus
Theoretical Computer Science
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Labelled Markov processes are continuous-state fully probabilistic labelled transition systems. They can be seen as co-algebras of a suitable monad on the category of measurable space. The theory as developed so far included a treatment of bisimulation, logical characterization of bisimulation, weak bisimulation, metrics, universal domains for LMPs and approximations. Much of the theory involved delicate properties of analytic spaces. Recently a new kind of averaging procedure was used to construct approximations. Remarkably, this version of the theory uses a dual view of LMPs and greatly simplifies the theory eliminating the need to consider aanlytic spaces. In this talk I will survey some of the ideas that led to this work.