9,897 research outputs found
MathMC: A mathematica-based tool for CSL model checking of deterministic and stochastic Petri nets
Deterministic and Stochastic Petri Nets (DSPNs) are a widely used high-level formalism for modeling discreteevent systems where events may occur either without consuming time, after a deterministic time, or after an exponentially distributed time. CSL (Continuous Stochastic Logic) is a (branching) temporal logic developed to express probabilistic properties in continuous time Markov chains (CTMCs). In this paper we present a Mathematica-based tool that implements recent developments for model checking CSL style properties on DSPNs. Furthermore, as a consequence of the type of process underlying DSPNs (a superset of Markovian processes), we are also able to check CSL properties of Generalized Stochastic Petri Nets (GSPNs) and labeled CTMCs
Model-checking branching-time properties of probabilistic automata and probabilistic one-counter automata
This paper studies the problem of model-checking of probabilistic automaton
and probabilistic one-counter automata against probabilistic branching-time
temporal logics (PCTL and PCTL). We show that it is undecidable for these
problems.
We first show, by reducing to emptiness problem of probabilistic automata,
that the model-checking of probabilistic finite automata against branching-time
temporal logics are undecidable. And then, for each probabilistic automata, by
constructing a probabilistic one-counter automaton with the same behavior as
questioned probabilistic automata the undecidability of model-checking problems
against branching-time temporal logics are derived, herein.Comment: Comments are welcom
Petri nets for systems and synthetic biology
We give a description of a Petri net-based framework for
modelling and analysing biochemical pathways, which uniĀÆes the qualita-
tive, stochastic and continuous paradigms. Each perspective adds its con-
tribution to the understanding of the system, thus the three approaches
do not compete, but complement each other. We illustrate our approach
by applying it to an extended model of the three stage cascade, which
forms the core of the ERK signal transduction pathway. Consequently
our focus is on transient behaviour analysis. We demonstrate how quali-
tative descriptions are abstractions over stochastic or continuous descrip-
tions, and show that the stochastic and continuous models approximate
each other. Although our framework is based on Petri nets, it can be
applied more widely to other formalisms which are used to model and
analyse biochemical networks
Variations of model checking
The logic ATCTL is a convenient logic to specify properties with actions and real-time. It is intended as a property language for Lightweight UML models [12], which consist mainly of simplified class diagrams and statecharts. ATCTL combines two known extensions of CTL, namely ACTL and TCTL. The reason to extend CTL with both actions and real time is that in LUML stateĀætransition diagrams, we specify states, actions and real time, and our properties refer to all of these elements. The analyst therefore needs a property language that contains constructs for all these elements. ATCTL can be reduced to ACTL as well as to TCTL, and therefore also to CTL. This gives us a choice of tools for model checking; we have used is Kronos [13], a TCTL model checker
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A Monte Carlo model checker for probabilistic LTL with numerical constraints
We define the syntax and semantics of a new temporal logic called probabilistic LTL with numerical constraints (PLTLc).
We introduce an efficient model checker for PLTLc properties. The efficiency of the model checker is through approximation
using Monte Carlo sampling of finite paths through the modelās state space (simulation outputs) and parallel model checking
of the paths. Our model checking method can be applied to any model producing quantitative output ā continuous or
stochastic, including those with complex dynamics and those with an infinite state space. Furthermore, our offline approach
allows the analysis of observed (real-life) behaviour traces. We find in this paper that PLTLc properties with constraints
over free variables can replace full model checking experiments, resulting in a significant gain in efficiency. This overcomes
one disadvantage of model checking experiments which is that the complexity depends on system granularity and number of
variables, and quickly becomes infeasible. We focus on models of biochemical networks, and specifically in this paper on
intracellular signalling pathways; however our method can be applied to a wide range of biological as well as technical
systems and their models. Our work contributes to the emerging field of synthetic biology by proposing a rigourous approach
for the structured formal engineering of biological systems
Tableaux for Policy Synthesis for MDPs with PCTL* Constraints
Markov decision processes (MDPs) are the standard formalism for modelling
sequential decision making in stochastic environments. Policy synthesis
addresses the problem of how to control or limit the decisions an agent makes
so that a given specification is met. In this paper we consider PCTL*, the
probabilistic counterpart of CTL*, as the specification language. Because in
general the policy synthesis problem for PCTL* is undecidable, we restrict to
policies whose execution history memory is finitely bounded a priori.
Surprisingly, no algorithm for policy synthesis for this natural and
expressive framework has been developed so far. We close this gap and describe
a tableau-based algorithm that, given an MDP and a PCTL* specification, derives
in a non-deterministic way a system of (possibly nonlinear) equalities and
inequalities. The solutions of this system, if any, describe the desired
(stochastic) policies.
Our main result in this paper is the correctness of our method, i.e.,
soundness, completeness and termination.Comment: This is a long version of a conference paper published at TABLEAUX
2017. It contains proofs of the main results and fixes a bug. See the
footnote on page 1 for detail
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