989 research outputs found
On the possible Computational Power of the Human Mind
The aim of this paper is to address the question: Can an artificial neural
network (ANN) model be used as a possible characterization of the power of the
human mind? We will discuss what might be the relationship between such a model
and its natural counterpart. A possible characterization of the different power
capabilities of the mind is suggested in terms of the information contained (in
its computational complexity) or achievable by it. Such characterization takes
advantage of recent results based on natural neural networks (NNN) and the
computational power of arbitrary artificial neural networks (ANN). The possible
acceptance of neural networks as the model of the human mind's operation makes
the aforementioned quite relevant.Comment: Complexity, Science and Society Conference, 2005, University of
Liverpool, UK. 23 page
Pre-automata as Mathematical Models of Event Flows Recognisers
The new class of recognisers is introduced and studied in the
paper. The models are based on the notion of partial action of a free nite
generated monoid. Authors called such models by preautomata. Some
properties of preautomata were established and proved in the paper.
These properties allow to consider the pre-automata as mathematical
models of recognizers of event
ows in processes of the interaction of
software systems
Networks of Bio-inspired Processors
The goal of this work is twofold. Firstly, we propose a uniform view of three types of accepting networks of bio-inspired processors: networks of evolutionary processors, networks of splicing processors and networks of genetic processors. And, secondly, we survey some features of these networks: computational power, computational and descriptional complexity, the existence of universal networks, eciency as problem solvers and the relationships among them
Features and Fluents for Logic Programming: Non-simulative Algebraic Semantics
A Non-simulative Algebraic Semantics is defined and its range of applicability
is proven to be the K-RACi class of the Features and Fluents framework.
The comparative assessment reveals the semantics epistemologically equivalent
and ontologically stronger than the Abductive Logic Programming, the
Action Description Language A and the PMON entailment. The semantics
is shown to be decidable
Transducers based on networks of evolutionary processors LOS FINANCIADORES NO ESTÁN BIEN
We consider a new type of transducer that does not scan sequentially the input word. Instead, it consists of a directed graph whose nodes are processors which work in parallel and are specialized in just one type of a very simple evolutionary operation: inserting, deleting or substituting a symbol by another one. The computation on an input word starts with this word placed in a designated node, the input node, of the network an alternates evolutionary and communication steps. The computation halts as soon as another designated node, the output node, is nonempty. The translation of the input word is the set of words existing in the output node when the computation halts. We prove that these transducers can simulate the work of generalized sequential machines on every input. Furthermore, all words obtained by a given generalized sequential machine by the shortest computations on a given word can also be computed by the new transducers. Unlike the case of generalized sequential machines, every recursively enumerable language can be the transduction de?ned by the new transducer of a very simple regular language. The same idea may be used for proving that these transducers can simulate the shortest computations of an arbitrary Turing machine, used as a transducer, on every input word. Finally, we consider a restricted variant of NEP transducer, namely pure NEP transducers and prove that there are still regular languages whose pure NEP transductions are not semilinear
Changing a semantics: opportunism or courage?
The generalized models for higher-order logics introduced by Leon Henkin, and
their multiple offspring over the years, have become a standard tool in many
areas of logic. Even so, discussion has persisted about their technical status,
and perhaps even their conceptual legitimacy. This paper gives a systematic
view of generalized model techniques, discusses what they mean in mathematical
and philosophical terms, and presents a few technical themes and results about
their role in algebraic representation, calibrating provability, lowering
complexity, understanding fixed-point logics, and achieving set-theoretic
absoluteness. We also show how thinking about Henkin's approach to semantics of
logical systems in this generality can yield new results, dispelling the
impression of adhocness. This paper is dedicated to Leon Henkin, a deep
logician who has changed the way we all work, while also being an always open,
modest, and encouraging colleague and friend.Comment: 27 pages. To appear in: The life and work of Leon Henkin: Essays on
his contributions (Studies in Universal Logic) eds: Manzano, M., Sain, I. and
Alonso, E., 201
- …