13,487 research outputs found
Lattice Gas Automata for Reactive Systems
Reactive lattice gas automata provide a microscopic approachto the dynamics
of spatially-distributed reacting systems. After introducing the subject within
the wider framework of lattice gas automata (LGA) as a microscopic approach to
the phenomenology of macroscopic systems, we describe the reactive LGA in terms
of a simple physical picture to show how an automaton can be constructed to
capture the essentials of a reactive molecular dynamics scheme. The statistical
mechanical theory of the automaton is then developed for diffusive transport
and for reactive processes, and a general algorithm is presented for reactive
LGA. The method is illustrated by considering applications to bistable and
excitable media, oscillatory behavior in reactive systems, chemical chaos and
pattern formation triggered by Turing bifurcations. The reactive lattice gas
scheme is contrasted with related cellular automaton methods and the paper
concludes with a discussion of future perspectives.Comment: to appear in PHYSICS REPORTS, 81 revtex pages; uuencoded gziped
postscript file; figures available from [email protected] or
[email protected]
Minimization of Reactive Probabilistic Automata
The problem of finite automata minimization is important for software and hardware designing. Different
types of automata are used for modeling systems or machines with finite number of states. The limitation of
number of states gives savings in resources and time. In this article we show specific type of probabilistic
automata: the reactive probabilistic finite automata with accepting states (in brief the reactive probabilistic
automata), and definitions of languages accepted by it. We present definition of bisimulation relation for
automata's states and define relation of indistinguishableness of automata states, on base of which we could
effectuate automata minimization. Next we present detailed algorithm reactive probabilistic automata’s
minimization with determination of its complexity and analyse example solved with help of this algorithm
Exploiting the Temporal Logic Hierarchy and the Non-Confluence Property for Efficient LTL Synthesis
The classic approaches to synthesize a reactive system from a linear temporal
logic (LTL) specification first translate the given LTL formula to an
equivalent omega-automaton and then compute a winning strategy for the
corresponding omega-regular game. To this end, the obtained omega-automata have
to be (pseudo)-determinized where typically a variant of Safra's
determinization procedure is used. In this paper, we show that this
determinization step can be significantly improved for tool implementations by
replacing Safra's determinization by simpler determinization procedures. In
particular, we exploit (1) the temporal logic hierarchy that corresponds to the
well-known automata hierarchy consisting of safety, liveness, Buechi, and
co-Buechi automata as well as their boolean closures, (2) the non-confluence
property of omega-automata that result from certain translations of LTL
formulas, and (3) symbolic implementations of determinization procedures for
the Rabin-Scott and the Miyano-Hayashi breakpoint construction. In particular,
we present convincing experimental results that demonstrate the practical
applicability of our new synthesis procedure
Learning Markov Decision Processes for Model Checking
Constructing an accurate system model for formal model verification can be
both resource demanding and time-consuming. To alleviate this shortcoming,
algorithms have been proposed for automatically learning system models based on
observed system behaviors. In this paper we extend the algorithm on learning
probabilistic automata to reactive systems, where the observed system behavior
is in the form of alternating sequences of inputs and outputs. We propose an
algorithm for automatically learning a deterministic labeled Markov decision
process model from the observed behavior of a reactive system. The proposed
learning algorithm is adapted from algorithms for learning deterministic
probabilistic finite automata, and extended to include both probabilistic and
nondeterministic transitions. The algorithm is empirically analyzed and
evaluated by learning system models of slot machines. The evaluation is
performed by analyzing the probabilistic linear temporal logic properties of
the system as well as by analyzing the schedulers, in particular the optimal
schedulers, induced by the learned models.Comment: In Proceedings QFM 2012, arXiv:1212.345
Towards a Uniform Theory of Effectful State Machines
Using recent developments in coalgebraic and monad-based semantics, we
present a uniform study of various notions of machines, e.g. finite state
machines, multi-stack machines, Turing machines, valence automata, and weighted
automata. They are instances of Jacobs' notion of a T-automaton, where T is a
monad. We show that the generic language semantics for T-automata correctly
instantiates the usual language semantics for a number of known classes of
machines/languages, including regular, context-free, recursively-enumerable and
various subclasses of context free languages (e.g. deterministic and real-time
ones). Moreover, our approach provides new generic techniques for studying the
expressivity power of various machine-based models.Comment: final version accepted by TOC
Interestingness of traces in declarative process mining: The janus LTLPf Approach
Declarative process mining is the set of techniques aimed at extracting behavioural constraints from event logs. These constraints are inherently of a reactive nature, in that their activation restricts the occurrence of other activities. In this way, they are prone to the principle of ex falso quod libet: they can be satisfied even when not activated. As a consequence, constraints can be mined that are hardly interesting to users or even potentially misleading. In this paper, we build on the observation that users typically read and write temporal constraints as if-statements with an explicit indication of the activation condition. Our approach is called Janus, because it permits the specification and verification of reactive constraints that, upon activation, look forward into the future and backwards into the past of a trace. Reactive constraints are expressed using Linear-time Temporal Logic with Past on Finite Traces (LTLp f). To mine them out of event logs, we devise a time bi-directional valuation technique based on triplets of automata operating in an on-line fashion. Our solution proves efficient, being at most quadratic w.r.t. trace length, and effective in recognising interestingness of discovered constraints
Synthesis of Data Word Transducers
In reactive synthesis, the goal is to automatically generate an
implementation from a specification of the reactive and non-terminating
input/output behaviours of a system. Specifications are usually modelled as
logical formulae or automata over infinite sequences of signals
(-words), while implementations are represented as transducers. In the
classical setting, the set of signals is assumed to be finite. In this paper,
we consider data -words instead, i.e., words over an infinite alphabet.
In this context, we study specifications and implementations respectively given
as automata and transducers extended with a finite set of registers. We
consider different instances, depending on whether the specification is
nondeterministic, universal or deterministic, and depending on whether the
number of registers of the implementation is given or not.
In the unbounded setting, we show undecidability for both universal and
nondeterministic specifications, while decidability is recovered in the
deterministic case. In the bounded setting, undecidability still holds for
nondeterministic specifications, but can be recovered by disallowing tests over
input data. The generic technique we use to show the latter result allows us to
reprove some known result, namely decidability of bounded synthesis for
universal specifications
Reactive Programming of Cellular Automata
Implementation of cellular automata using reactive programming gives a way to code cell behaviors in an abstract and modular way. Multiprocessing also becomes possible. The paper describes the implementation of cellular automata with the reactive programming language LOFT, a thread-based extension of C. Self replicating loops considered in artificial life are coded to show the interest of the approach
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