4,792 research outputs found
Multi-Head Finite Automata: Characterizations, Concepts and Open Problems
Multi-head finite automata were introduced in (Rabin, 1964) and (Rosenberg,
1966). Since that time, a vast literature on computational and descriptional
complexity issues on multi-head finite automata documenting the importance of
these devices has been developed. Although multi-head finite automata are a
simple concept, their computational behavior can be already very complex and
leads to undecidable or even non-semi-decidable problems on these devices such
as, for example, emptiness, finiteness, universality, equivalence, etc. These
strong negative results trigger the study of subclasses and alternative
characterizations of multi-head finite automata for a better understanding of
the nature of non-recursive trade-offs and, thus, the borderline between
decidable and undecidable problems. In the present paper, we tour a fragment of
this literature
Measuring Communication in Parallel Communicating Finite Automata
Systems of deterministic finite automata communicating by sending their
states upon request are investigated, when the amount of communication is
restricted. The computational power and decidability properties are studied for
the case of returning centralized systems, when the number of necessary
communications during the computations of the system is bounded by a function
depending on the length of the input. It is proved that an infinite hierarchy
of language families exists, depending on the number of messages sent during
their most economical recognitions. Moreover, several properties are shown to
be not semi-decidable for the systems under consideration.Comment: In Proceedings AFL 2014, arXiv:1405.527
P Colony Automata with LL(k)-like Conditions
We investigate the possibility of the deterministic parsing (that is, parsing
without backtracking) of languages characterized by (generalized) P colony automata.
We de ne a class of P colony automata satisfying a property which resembles the LL(k)
property of context-free grammars, and study the possibility of parsing the characterized
languages using a k symbol lookahead, as in the LL(k) parsing method for context-free
languages
Bounded Languages Meet Cellular Automata with Sparse Communication
Cellular automata are one-dimensional arrays of interconnected interacting
finite automata. We investigate one of the weakest classes, the real-time
one-way cellular automata, and impose an additional restriction on their
inter-cell communication by bounding the number of allowed uses of the links
between cells. Moreover, we consider the devices as acceptors for bounded
languages in order to explore the borderline at which non-trivial decidability
problems of cellular automata classes become decidable. It is shown that even
devices with drastically reduced communication, that is, each two neighboring
cells may communicate only constantly often, accept bounded languages that are
not semilinear. If the number of communications is at least logarithmic in the
length of the input, several problems are undecidable. The same result is
obtained for classes where the total number of communications during a
computation is linearly bounded
Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking
This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications
Development and validation of computational models of cellular interaction
In this paper we take the view that computational models of biological systems should satisfy two conditions –
they should be able to predict function at a systems biology level, and robust techniques of validation against
biological models must be available. A modelling paradigm for developing a predictive computational model of
cellular interaction is described, and methods of providing robust validation against biological models are
explored, followed by a consideration of software issues
On one-way cellular automata with a fixed number of cells
We investigate a restricted one-way cellular automaton (OCA) model where the number of cells is bounded by a constant number k, so-called kC-OCAs. In contrast to the general model, the generative capacity of the restricted model is reduced to the set of regular languages. A kC-OCA can be algorithmically converted to a deterministic finite automaton (DFA). The blow-up in the number of states is bounded by a polynomial of degree k. We can exhibit a family of unary languages which shows that this upper bound is tight in order of magnitude. We then study upper and lower bounds for the trade-off when converting DFAs to kC-OCAs. We show that there are regular languages where the use of kC-OCAs cannot reduce the number of states when compared to DFAs. We then investigate trade-offs between kC-OCAs with different numbers of cells and finally treat the problem of minimizing a given kC-OCA
On two-way communication in cellular automata with a fixed number of cells
The effect of adding two-way communication to k cells one-way cellular automata (kC-OCAs) on their size of description is studied. kC-OCAs are a parallel model for the regular languages that consists of an array of k identical deterministic finite automata (DFAs), called cells, operating in parallel. Each cell gets information from its right neighbor only. In this paper, two models with different amounts of two-way communication are investigated. Both models always achieve quadratic savings when compared to DFAs. When compared to a one-way cellular model, the result is that minimum two-way communication can achieve at most quadratic savings whereas maximum two-way communication may provide savings bounded by a polynomial of degree k
Implicit Simulations using Messaging Protocols
A novel algorithm for performing parallel, distributed computer simulations
on the Internet using IP control messages is introduced. The algorithm employs
carefully constructed ICMP packets which enable the required computations to be
completed as part of the standard IP communication protocol. After providing a
detailed description of the algorithm, experimental applications in the areas
of stochastic neural networks and deterministic cellular automata are
discussed. As an example of the algorithms potential power, a simulation of a
deterministic cellular automaton involving 10^5 Internet connected devices was
performed.Comment: 14 pages, 3 figure
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