Bisimulation through probabilistic testing
Information and Computation
Probabilistic simulations for probabilistic processes
Nordic Journal of Computing
Bisimulation for Probabilistic Transition Systems: A Coalgebraic Approach
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
Deriving Bisimulation Congruences for Reactive Systems
CONCUR '00 Proceedings of the 11th International Conference on Concurrency Theory
Automatic Verification of Real-Time Systems with Discrete Probability Distributions
ARTS '99 Proceedings of the 5th International AMAST Workshop on Formal Methods for Real-Time and Probabilistic Systems
Bisimulation for labelled Markov processes
Information and Computation - Special issue: LICS'97
Towards a Mathematical Operational Semantics
LICS '97 Proceedings of the 12th Annual IEEE Symposium on Logic in Computer Science
BioAmbients: an abstraction for biological compartments
Theoretical Computer Science - Special issue: Computational systems biology
Bisimulations in calculi modelling membranes
Formal Aspects of Computing
A simple calculus for proteins and cells
Theoretical Computer Science
Deriving Structural Labelled Transitions for Mobile Ambients
CONCUR '08 Proceedings of the 19th international conference on Concurrency Theory
Reactive Systems, Barbed Semantics, and the Mobile Ambients
FOSSACS '09 Proceedings of the 12th International Conference on Foundations of Software Science and Computational Structures: Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2009
Approximating Markov Processes by Averaging
ICALP '09 Proceedings of the 36th Internatilonal Collogquium on Automata, Languages and Programming: Part II
CoBiC: Context-dependent Bioambient Calculus
Electronic Notes in Theoretical Computer Science (ENTCS)
Bisimulation and cocongruence for probabilistic systems
Information and Computation - Special issue: Seventh workshop on coalgebraic methods in computer science 2004
Labelled Markov Processes
Stochastic Coalgebraic Logic
Stochastic simulation of biological systems with dynamical compartment structure
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Efficient, correct simulation of biological processes in the stochastic pi-calculus
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
The calculus of looping sequences for modeling biological membranes
WMC'07 Proceedings of the 8th international conference on Membrane computing
Approximating labelled Markov processes again!
CALCO'09 Proceedings of the 3rd international conference on Algebra and coalgebra in computer science
A generic abstract machine for stochastic process calculi
Proceedings of the 8th International Conference on Computational Methods in Systems Biology
The Measurable Space of Stochastic Processes
QEST '10 Proceedings of the 2010 Seventh International Conference on the Quantitative Evaluation of Systems
CMSB'04 Proceedings of the 20 international conference on Computational Methods in Systems Biology
Measurable stochastics for Brane Calculus
Theoretical Computer Science
A stochastic semantics for bioambients
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
Measurable stochastics for Brane Calculus
Theoretical Computer Science
| Hi-index | 5.23 |
The main aim of this work is to give a stochastic extension of the Brane Calculus, along the lines of recent work by Cardelli and Mardare (2010) [12]. In this approach, the semantics of a process is a measure of the stochastic distribution of possible derivations. To this end, we first introduce a compositional, finitely branching labelled transition system for Brane Calculus; interestingly, the associated strong bisimulation is a congruence. Then, we give a stochastic semantics to Brane systems by defining them as Markov processes over the measurable space generated by terms up-to syntactic congruence, and where the measures are indexed by the actions of this new LTS. Finally, we provide an SOS presentation of this stochastic semantics, which is compositional and syntax-driven, and moreover the induced rate bisimilarity is a congruence.