Automated compositional Markov chain generation for a plain-old telephone system
Science of Computer Programming
Automatic verification of real-time systems with discrete probability distributions
Theoretical Computer Science
Weak Bisimulation is Sound and Complete for PCTL*
CONCUR '02 Proceedings of the 13th International Conference on Concurrency Theory
FSPNs: Fluid Stochastic Petri Nets
Proceedings of the 14th International Conference on Application and Theory of Petri Nets
Discrete-event simulation of fluid stochastic Petri nets
PNPM '97 Proceedings of the 6th International Workshop on Petri Nets and Performance Models
Performance analysis of probabilistic timed automata using digital clocks
Formal Methods in System Design
Stochastic Optimal Control: The Discrete-Time Case
Stochastic Optimal Control: The Discrete-Time Case
Bisimulation for general stochastic hybrid systems
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
Polynomial stochastic hybrid systems
HSCC'05 Proceedings of the 8th international conference on Hybrid Systems: computation and control
A Formal Framework for User Centric Control of Probabilistic Multi-agent Cyber-Physical Systems
Computational Logic in Multi-Agent Systems
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Recently, there is an explosive development of fluid approa- ches to computer and distributed systems. These approaches are inherently stochastic and generate continuous state space models. Usually, the performance measures for these systems are defined using probabilities of reaching certain sets of the state space. These measures are well understood in the discrete context and many efficient model checking procedures have been developed for specifications involving them. The continuous case is far more complicated and new methods are necessary. In this paper we propose a general model checking strategy founded on advanced concepts and results of stochastic analysis. Due to the problem complexity, in this paper, we achieve the first necessary step of characterizing mathematically the problem. We construct upper bounds for the performance measures using Martin capacities. We introduce a concept of bisimulation that preserves the performance measures and a metric that characterizes the bisimulation