238 research outputs found
Bisimulation, Logic and Reachability Analysis for Markovian Systems
In the recent years, there have been a large amount of investigations on safety verification of uncertain continuous systems. In engineering and applied mathematics, this verification is called stochastic reachability analysis, while in computer science this is called probabilistic model checking
(PMC). In the context of this work, we consider the two terms interchangeable. It is worthy to note that PMC has been mostly considered for discrete systems. Therefore, there is an issue of improving the application of computer science techniques in the formal verification of continuous stochastic systems.
We present a new probabilistic logic of model theoretic nature. The terms of this logic express reachability properties and the logic formulas express statistical properties of terms.
Moreover, we show that this logic characterizes a bisimulation relation for continuous time continuous space Markov processes. For this logic we define a new semantics using state space symmetries. This is a recent concept that was successfully used in model checking. Using this semantics, we prove a full abstraction result. Furthermore, we prove a result that can be used in model checking, namely that the bisimulation preserves the probabilities of the reachable sets
Bisimulations and Logical Characterizations on Continuous-time Markov Decision Processes
In this paper we study strong and weak bisimulation equivalences for
continuous-time Markov decision processes (CTMDPs) and the logical
characterizations of these relations with respect to the continuous-time
stochastic logic (CSL). For strong bisimulation, it is well known that it is
strictly finer than CSL equivalence. In this paper we propose strong and weak
bisimulations for CTMDPs and show that for a subclass of CTMDPs, strong and
weak bisimulations are both sound and complete with respect to the equivalences
induced by CSL and the sub-logic of CSL without next operator respectively. We
then consider a standard extension of CSL, and show that it and its sub-logic
without X can be fully characterized by strong and weak bisimulations
respectively over arbitrary CTMDPs.Comment: The conference version of this paper was published at VMCAI 201
Model Checking Markov Chains with Actions and State Labels
In the past, logics of several kinds have been proposed for reasoning about discrete- or continuous-time Markov chains. Most of these logics rely on either state labels (atomic propositions) or on transition labels (actions). However, in several applications it is useful to reason about both state-properties and action-sequences. For this purpose, we introduce the logic asCSL which provides powerful means to characterize execution paths of Markov chains with actions and state labels. asCSL can be regarded as an extension of the purely state-based logic asCSL (continuous stochastic logic). \ud
In asCSL, path properties are characterized by regular expressions over actions and state-formulas. Thus, the truth value of path-formulas does not only depend on the available actions in a given time interval, but also on the validity of certain state formulas in intermediate states.\ud
We compare the expressive power of CSL and asCSL and show that even the state-based fragment of asCSL is strictly more expressive than CSL if time intervals starting at zero are employed. Using an automaton-based technique, an asCSL formula and a Markov chain with actions and state labels are combined into a product Markov chain. For time intervals starting at zero we establish a reduction of the model checking problem for asCSL to CSL model checking on this product Markov chain. The usefulness of our approach is illustrated by through an elaborate model of a scalable cellular communication system for which several properties are formalized by means of asCSL-formulas, and checked using the new procedure
A theory for the semantics of stochastic and non-deterministic continuous systems
Preprint de capĂtulo del libro Lecture Notes in Computer Science book series (LNCS, volume 8453)The description of complex systems involving physical or biological components usually requires to model complex continuous behavior induced by variables such as time, distance, speed, temperature, alkalinity of a solution, etc. Often, such variables can be quantified probabilistically to better understand the behavior of the complex systems. For example, the arrival time of events may be considered a Poisson process or the weight of an individual may be assumed to be distributed according to a log-normal distribution. However, it is also common that the uncertainty on how these variables behave makes us prefer to leave out the choice of a particular probability and rather model it as a purely non-deterministic decision, as it is the case when a system is intended to be deployed in a variety of very different computer or network architectures. Therefore, the semantics of these systems needs to be represented by a variant of probabilistic automata that involves continuous domains on the state space and the transition relation. In this paper, we provide a survey on the theory of such kind of models. We present the theory of the so-called labeled Markov processes (LMP) and its extension with internal non-determinism (NLMP). We show that in these complex domains, the bisimulation relation can be understood in different manners. We show the relation between the different bisimulations and try to understand their expressiveness through examples. We also study variants of Hennessy-Milner logic thatprovides logical characterizations of some of these bisimulations.Supported by ANPCyT project PICT-2012-1823, SeCyT-UNC projects 05/B284 and 05/B497 and program 05/BP02, and EU 7FP grant agreement 295261 (MEALS).http://link.springer.com/chapter/10.1007%2F978-3-662-45489-3_3acceptedVersionFil: Budde, Carlos Esteban. Universidad Nacional de CĂłrdoba. Facultad de MatemĂĄtica, AstronomĂa y FĂsica; Argentina.Fil: Budde, Carlos Esteban. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina.Fil: D'Argenio, Pedro RubĂ©n. Universidad Nacional de CĂłrdoba. Facultad de MatemĂĄtica, AstronomĂa y FĂsica; Argentina.Fil: D'Argenio, Pedro RubĂ©n. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina.Fil: SĂĄnchez Terraf, Pedro Octavio. Universidad Nacional de CĂłrdoba. Facultad de MatemĂĄtica, AstronomĂa y FĂsica; Argentina.Fil: SĂĄnchez Terraf, Pedro Octavio. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentina.Fil: Wolovick, NicolĂĄs. Universidad Nacional de CĂłrdoba. Facultad de MatemĂĄtica, AstronomĂa y FĂsica; Argentina.EstadĂstica y Probabilida
Bisimulation for Labelled Markov Processes
AbstractIn this paper we introduce a new class of labelled transition systemsâlabelled Markov processesâ and define bisimulation for them. Labelled Markov processes are probabilistic labelled transition systems where the state space is not necessarily discrete. We assume that the state space is a certain type of common metric space called an analytic space. We show that our definition of probabilistic bisimulation generalizes the LarsenâSkou definition given for discrete systems. The formalism and mathematics is substantially different from the usual treatment of probabilistic process algebra. The main technical contribution of the paper is a logical characterization of probabilistic bisimulation. This study revealed some unexpected results, even for discrete probabilistic systems. âąBisimulation can be characterized by a very weak modal logic. The most striking feature is that one has no negation or any kind of negative proposition.âąWe do not need any finite branching assumption, yet there is no need of infinitary conjunction.
We also show how to construct the maximal autobisimulation on a system. In the finite state case, this is just a state minimization construction. The proofs that we give are of an entirely different character than the typical proofs of these results. They use quite subtle facts about analytic spaces and appear, at first sight, to be entirely nonconstructive. Yet one can give an algorithm for deciding bisimilarity of finite state systems which constructs a formula that witnesses the failure of bisimulation
Measurable Stochastics for Brane Calculus
We give a stochastic extension of the Brane Calculus, along the lines of
recent work by Cardelli and Mardare. In this presentation, the semantics of a
Brane process is a measure of the stochastic distribution of possible
derivations. To this end, we first introduce a labelled transition system for
Brane Calculus, proving its adequacy w.r.t. the usual reduction semantics.
Then, brane systems are presented 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 a SOS presentation
of this stochastic semantics, which is compositional and syntax-driven.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
Verification of Confidentiality of Multi-threaded Programs
An introduction of Slalom project: motivation, plans and some result
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