376 research outputs found
Real-time and Probabilistic Temporal Logics: An Overview
Over the last two decades, there has been an extensive study on logical
formalisms for specifying and verifying real-time systems. Temporal logics have
been an important research subject within this direction. Although numerous
logics have been introduced for the formal specification of real-time and
complex systems, an up to date comprehensive analysis of these logics does not
exist in the literature. In this paper we analyse real-time and probabilistic
temporal logics which have been widely used in this field. We extrapolate the
notions of decidability, axiomatizability, expressiveness, model checking, etc.
for each logic analysed. We also provide a comparison of features of the
temporal logics discussed
Petri nets for systems and synthetic biology
We give a description of a Petri net-based framework for
modelling and analysing biochemical pathways, which uni¯es 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
Towards Cancer Hybrid Automata
This paper introduces Cancer Hybrid Automata (CHAs), a formalism to model the
progression of cancers through discrete phenotypes. The classification of
cancer progression using discrete states like stages and hallmarks has become
common in the biology literature, but primarily as an organizing principle, and
not as an executable formalism. The precise computational model developed here
aims to exploit this untapped potential, namely, through automatic verification
of progression models (e.g., consistency, causal connections, etc.),
classification of unreachable or unstable states and computer-generated
(individualized or universal) therapy plans. The paper builds on a
phenomenological approach, and as such does not need to assume a model for the
biochemistry of the underlying natural progression. Rather, it abstractly
models transition timings between states as well as the effects of drugs and
clinical tests, and thus allows formalization of temporal statements about the
progression as well as notions of timed therapies. The model proposed here is
ultimately based on hybrid automata, and we show how existing controller
synthesis algorithms can be generalized to CHA models, so that therapies can be
generated automatically. Throughout this paper we use cancer hallmarks to
represent the discrete states through which cancer progresses, but other
notions of discretely or continuously varying state formalisms could also be
used to derive similar therapies.Comment: In Proceedings HSB 2012, arXiv:1208.315
Approximate Model Checking of Real-Time Systems for Linear Duration Invariants
Real-time systems are usually modelled with timed automata and real-time requirements relating to the state durations of the system are
often specifiable using Linear Duration Invariants, which is a decidable subclass of Duration Calculus formulas. Various algorithms have been developed
to check timed automata or real-time automata for linear duration invariants, but each needs complicated preprocessing and exponential calculation.
To the best of our knowledge, these algorithms have not been implemented. In this paper, we present an approximate model checking technique based
on a genetic algorithm to check real-time automata for linear durration invariants in reasonable times. Genetic algorithm is a good optimization
method when a problem needs massive computation and it works particularly well in our case because the fitness function which is derived from the
linear duration invariant is linear. ACM Computing Classification System (1998): D.2.4, C.3
Satisfiability Games for Branching-Time Logics
The satisfiability problem for branching-time temporal logics like CTL*, CTL
and CTL+ has important applications in program specification and verification.
Their computational complexities are known: CTL* and CTL+ are complete for
doubly exponential time, CTL is complete for single exponential time. Some
decision procedures for these logics are known; they use tree automata,
tableaux or axiom systems. In this paper we present a uniform game-theoretic
framework for the satisfiability problem of these branching-time temporal
logics. We define satisfiability games for the full branching-time temporal
logic CTL* using a high-level definition of winning condition that captures the
essence of well-foundedness of least fixpoint unfoldings. These winning
conditions form formal languages of \omega-words. We analyse which kinds of
deterministic {\omega}-automata are needed in which case in order to recognise
these languages. We then obtain a reduction to the problem of solving parity or
B\"uchi games. The worst-case complexity of the obtained algorithms matches the
known lower bounds for these logics. This approach provides a uniform, yet
complexity-theoretically optimal treatment of satisfiability for branching-time
temporal logics. It separates the use of temporal logic machinery from the use
of automata thus preserving a syntactical relationship between the input
formula and the object that represents satisfiability, i.e. a winning strategy
in a parity or B\"uchi game. The games presented here work on a Fischer-Ladner
closure of the input formula only. Last but not least, the games presented here
come with an attempt at providing tool support for the satisfiability problem
of complex branching-time logics like CTL* and CTL+
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