538 research outputs found
A Survey on Continuous Time Computations
We provide an overview of theories of continuous time computation. These
theories allow us to understand both the hardness of questions related to
continuous time dynamical systems and the computational power of continuous
time analog models. We survey the existing models, summarizing results, and
point to relevant references in the literature
Dimensions of Neural-symbolic Integration - A Structured Survey
Research on integrated neural-symbolic systems has made significant progress
in the recent past. In particular the understanding of ways to deal with
symbolic knowledge within connectionist systems (also called artificial neural
networks) has reached a critical mass which enables the community to strive for
applicable implementations and use cases. Recent work has covered a great
variety of logics used in artificial intelligence and provides a multitude of
techniques for dealing with them within the context of artificial neural
networks. We present a comprehensive survey of the field of neural-symbolic
integration, including a new classification of system according to their
architectures and abilities.Comment: 28 page
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
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
Beyond Markov Chains, Towards Adaptive Memristor Network-based Music Generation
We undertook a study of the use of a memristor network for music generation,
making use of the memristor's memory to go beyond the Markov hypothesis. Seed
transition matrices are created and populated using memristor equations, and
which are shown to generate musical melodies and change in style over time as a
result of feedback into the transition matrix. The spiking properties of simple
memristor networks are demonstrated and discussed with reference to
applications of music making. The limitations of simulating composing memristor
networks in von Neumann hardware is discussed and a hardware solution based on
physical memristor properties is presented.Comment: 22 pages, 13 pages, conference pape
Notes About Spiking Neural P Systems
Spiking neural P systems (SN P systems, for short) are much investigated
in the last years in membrane computing, but still many open problems and research
topics are open in this area. Here, we first recall two such problems (both related to
neural biology) from. One of them asks to build an SN P system able to store a
number, and to provide it to a reader without losing it, so that the number is available
for a further reading. We build here such a memory module and we discuss its extension
to model/implement more general operations, specific to (simple) data bases. Then, we
formulate another research issue, concerning pattern recognition in terms of SN P systems. In the context, we define a recent version of SN P systems, enlarged with rules able
to request spikes from the environment; based on this version, so-called SN dP systems
were recently introduced, extending to neural P systems the idea of a distributed dP
automaton. Some details about such devices are also given, as a further invitation to the
reader to this area of research.Junta de Andalucía P08 – TIC 0420
Spiking Neural dP Systems
We bring together two topics recently introduced in membrane computing,
the much investigated spiking neural P systems (in short, SN P systems), inspired from
the way the neurons communicate through spikes, and the dP systems (distributed P
systems, with components which "read" strings from the environment and then cooperate
in accepting their concatenation). The goal is to introduce SN dP systems, and to this
aim we first introduce SN P systems with the possibility to input, at their request, spikes
from the environment; this is done by so-called request rules. A preliminary investigation
of the obtained SN dP systems (they can also be called automata) is carried out. As
expected, request rules are useful, while the distribution in terms of dP systems can
handle languages which cannot be generated by usual SN P systems. We always work
with extended SN P systems; the non-extended case, as well as several other natural
questions remain open.Junta de Andalucía P08 – TIC 0420
Spiking Neural P Systems. Recent Results, Research Topics
After a quick introduction of spiking neural P systems (a class of P systems
inspired from the way neurons communicate by means of spikes, electrical impulses
of identical shape), and presentation of typical results (in general equivalence
with Turing machines as number computing devices, but also other issues, such as
the possibility of handling strings or infinite sequences), we present a long list of
open problems and research topics in this area, also mentioning recent attempts to
address some of them. The bibliography completes the information offered to the
reader interested in this research area.Ministerio de Educación y Ciencia TIN2006-13425Junta de Andalucía TIC-58
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