2,437 research outputs found
Partially Ordered Two-way B\"uchi Automata
We introduce partially ordered two-way B\"uchi automata and characterize
their expressive power in terms of fragments of first-order logic FO[<].
Partially ordered two-way B\"uchi automata are B\"uchi automata which can
change the direction in which the input is processed with the constraint that
whenever a state is left, it is never re-entered again. Nondeterministic
partially ordered two-way B\"uchi automata coincide with the first-order
fragment Sigma2. Our main contribution is that deterministic partially ordered
two-way B\"uchi automata are expressively complete for the first-order fragment
Delta2. As an intermediate step, we show that deterministic partially ordered
two-way B\"uchi automata are effectively closed under Boolean operations.
A small model property yields coNP-completeness of the emptiness problem and
the inclusion problem for deterministic partially ordered two-way B\"uchi
automata.Comment: The results of this paper were presented at CIAA 2010; University of
Stuttgart, Computer Scienc
Deterministic Autopoietic Automata
This paper studies two issues related to the paper on Computing by
Self-reproduction: Autopoietic Automata by Jiri Wiedermann. It is shown that
all results presented there extend to deterministic computations. In
particular, nondeterminism is not needed for a lineage to generate all
autopoietic automata
Using Sat solvers for synchronization issues in partial deterministic automata
We approach the task of computing a carefully synchronizing word of minimum
length for a given partial deterministic automaton, encoding the problem as an
instance of SAT and invoking a SAT solver. Our experimental results demonstrate
that this approach gives satisfactory results for automata with up to 100
states even if very modest computational resources are used.Comment: 15 pages, 3 figure
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
Attack-Resilient Supervisory Control of Discrete-Event Systems
In this work, we study the problem of supervisory control of discrete-event
systems (DES) in the presence of attacks that tamper with inputs and outputs of
the plant. We consider a very general system setup as we focus on both
deterministic and nondeterministic plants that we model as finite state
transducers (FSTs); this also covers the conventional approach to modeling DES
as deterministic finite automata. Furthermore, we cover a wide class of attacks
that can nondeterministically add, remove, or rewrite a sensing and/or
actuation word to any word from predefined regular languages, and show how such
attacks can be modeled by nondeterministic FSTs; we also present how the use of
FSTs facilitates modeling realistic (and very complex) attacks, as well as
provides the foundation for design of attack-resilient supervisory controllers.
Specifically, we first consider the supervisory control problem for
deterministic plants with attacks (i) only on their sensors, (ii) only on their
actuators, and (iii) both on their sensors and actuators. For each case, we
develop new conditions for controllability in the presence of attacks, as well
as synthesizing algorithms to obtain FST-based description of such
attack-resilient supervisors. A derived resilient controller provides a set of
all safe control words that can keep the plant work desirably even in the
presence of corrupted observation and/or if the control words are subjected to
actuation attacks. Then, we extend the controllability theorems and the
supervisor synthesizing algorithms to nondeterministic plants that satisfy a
nonblocking condition. Finally, we illustrate applicability of our methodology
on several examples and numerical case-studies
Computing with cells: membrane systems - some complexity issues.
Membrane computing is a branch of natural computing which abstracts computing models from the structure and the functioning of the living cell. The main ingredients of membrane systems, called P systems, are (i) the membrane structure, which consists of a hierarchical arrangements of membranes which delimit compartments where (ii) multisets of symbols, called objects, evolve according to (iii) sets of rules which are localised and associated with compartments. By using the rules in a nondeterministic/deterministic maximally parallel manner, transitions between the system configurations can be obtained. A sequence of transitions is a computation of how the system is evolving. Various ways of controlling the transfer of objects from one membrane to another and applying the rules, as well as possibilities to dissolve, divide or create membranes have been studied. Membrane systems have a great potential for implementing massively concurrent systems in an efficient way that would allow us to solve currently intractable problems once future biotechnology gives way to a practical bio-realization. In this paper we survey some interesting and fundamental complexity issues such as universality vs. nonuniversality, determinism vs. nondeterminism, membrane and alphabet size hierarchies, characterizations of context-sensitive languages and other language classes and various notions of parallelism
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