• Corpus ID: 15336495

Computers and Symbols versus Nets and Neurons

  title={Computers and Symbols versus Nets and Neurons},
  author={NeuronsKevin Gurney and Kevin N. Gurney},
1 These notes are currently under review for publication by UCL Press Limited in the UK. Duplication of this draft is permitted by individuals for personal use only. A n y other form of duplication or reproduction requires prior written permission of the author. This statement m ust be easily visible on the rst page of any reproduced copies. I would be happy to receive a n y comments you might h a ve on this draftt send them to me via electronic mail at Kevin.Gurney@brunel.ac.uk. I am… 

A reinforcement learning technique for enhancing human behavior models in a context-based architecture

The results obtained from this research show that behavior models built in a context-based framework can be enhanced by learning and reflecting the constraints in the environment.



An introduction to computing with neural nets

This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components.

Self-organization of orientation sensitive cells in the striate cortex

A nerve net model for the visual cortex of higher vertebrates is presented. A simple learning procedure is shown to be sufficient for the organization of some essential functional properties of

Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors

It is shown how experience can retune feature detectors to respond to a prescribed convex set of spatial patterns, and a classification of adult feature detector properties in terms of a small number of functional principles is suggested.

Cognitron: A self-organizing multilayered neural network

  • K. Fukushima
  • Computer Science, Biology
    Biological Cybernetics
  • 2004
A new hypothesis for the organization of synapses between neurons is proposed: “The synapse from neuron x to neuron y is reinforced when x fires provided that no neuron in the vicinity of y is firing stronger than y”, and a new algorithm with which a multilayered neural network is effectively organized can be deduced.

“Neural” computation of decisions in optimization problems

Results of computer simulations of a network designed to solve a difficult but well-defined optimization problem-the Traveling-Salesman Problem-are presented and used to illustrate the computational power of the networks.

A logical calculus of the ideas immanent in nervous activity

It is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under the other and gives the same results, although perhaps not in the same time.

On the proper treatment of connectionism

Abstract A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive

The General and Logical Theory of Au-tomata

I have to ask your forbearance for appearing here, since I am an outsider to most of the fields which form the subject of this conference. Even in the area in which I have some experience, that of