Continuous Attractor Neural Networks

Continuous Attractor Neural Networks

Thomas P. Trappenberg (Dalhousie University, Canada)
Copyright: © 2005 |Pages: 28
DOI: 10.4018/978-1-59140-312-8.ch016
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In this chapter a brief review is given of computational systems that are motivated by information processing in the brain, an area that is often called neurocomputing or artificial neural networks. While this is now a well studied and documented area, specific emphasis is given to a subclass of such models, called continuous attractor neural networks, which are beginning to emerge in a wide context of biologically inspired computing. The frequent appearance of such models in biologically motivated studies of brain functions gives some indication that this model might capture important information processing mechanisms used in the brain, either directly or indirectly. Most of this chapter is dedicated to an introduction to this basic model and some extensions that might be important for their application, either as a model of brain processing, or in technical applications. Direct technical applications are only emerging slowly, but some examples of promising directions are highlighted in this chapter.

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Table of Contents
Moshe Sipper
Leandro Nunes de Castro, Fernando J. Von Zuben
Chapter 1
Leandro Nunes de Castro, Fernando J. Von Zuben
Biologically inspired computing is just one of the branches of natural computing, which also encompasses artificial life, fractal geometry and... Sample PDF
From Biologically Inspired Computing to Natural Computing
Chapter 2
Penousal Machado, Francisco B. Pereira, Jorge Tavares, Ernesto Costa, Amílcar Cardoso
In this chapter we study the feasibility of using Turing Machines as a model for the evolution of computer programs. To assess this idea we select... Sample PDF
Evolutionary Turing Machines: The Quest for Busy Beavers
Chapter 3
Fabiano Luis de Sousa, Fernando Manuel Ramos, Roberto Luiz Galski, Issamu Muraoka
In this chapter a recently proposed meta-heuristic devised to be used in complex optimization problems is presented. Called Generalized Extremal... Sample PDF
Generalized External Optimization: A New Meta-Heuristic Inspired by a Model of Natural Evolution
Chapter 4
Taro Yabuki, Hitoshi Iba
In this chapter, a new representation scheme for Genetic Programming (GP) is proposed. We need a Turing-complete representation for a general method... Sample PDF
Genetic Programming Using a Turing-Complete Representation: Recurrent Network Consisting of Trees
Chapter 5
Cândida Ferreira
In this chapter an artificial problem solver inspired in natural genotype/phenotype systems — gene expression programming — is presented. As an... Sample PDF
Gene Expression Programming and the Evolution of Computer Programs
Chapter 6
Vincenzo Cutello, Giuseppe Nicosia
The chapter describes the theory of clonal selection and its usage in designing and implementing immunological algorithms for problem solving and... Sample PDF
The Clonal Selection Principle for In Silico and In Vitro Computing
Chapter 7
Sergio Alonso, Oscar Cordon, Iñaki Fernández de Viana, Francisco Herrera
This chapter introduces two different ways to integrate Evolutionary Computation Components in Ant Colony Optimization (ACO) Meta-heuristic. First... Sample PDF
Integrating Evolutionary Computation Components in Ant Colony Optimization
Chapter 8
Gurdip Singh, Sanjoy Das, Shekhar V. Gosavi, Sandeep Pujar
This chapter introduces ant colony optimization as a method for computing minimum Steiner trees in graphs. Tree computation is achieved when... Sample PDF
Ant Colony Algorithms for Steiner Trees: An Application to Routing in Sensor Networks
Chapter 9
Vahid Sherafat, Leandro Nunes de Castro, Eduardo Raul Hruschka
Algorithms inspired by the collective behavior of social organisms, from insect colonies to human societies, promoted the emergence of a new field... Sample PDF
The Influence of Pheromone and Adaptive Vision in the Standard Ant Clustering Algorithm
Chapter 10
James Kennedy
Particle swarm optimization is a computer paradigm that is based on human social influence and cognition. Candidate problem solutions are randomly... Sample PDF
Particle Swarms: Optimization Based on Sociocognition
Chapter 11
Angelo Loula, Ricardo Gudwin, Sidarta Ribeiro, Ivan de Araujo, João Queiroz
Here we propose, based on the Peircean semiotics and informed by neuroethological constraints, a methodology to simulate the emergence of symbolic... Sample PDF
Synthetic Approach to Semiotic Artificial Creatures
Chapter 12
Jean-Philippe Rennard
This chapter introduces the twin deadlocks of strong artificial life. Conceptualization of life is a deadlock both because of the existence of a... Sample PDF
Perspectives for Strong Artificial Life
Chapter 13
Peter J. Bentley
Fractal proteins are a new evolvable method of mapping genotype to phenotype through a developmental process, where genes are expressed into... Sample PDF
Controlling Robots with Fractal Gene Regulatory Networks
Chapter 14
Mark Neal, Jon Timmis
The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is... Sample PDF
Once More Unto the Breach: Towards Artificial Homeostasis
Chapter 15
C. Ronald Kube, Chris A.C. Parker, Tao Wang, Hong Zhang
In this chapter, we review our recent research in the area of collective robotics, and the problem of controlling multiple robots in the completion... Sample PDF
Biologically Inspired Collective Robotics
Chapter 16
Thomas P. Trappenberg
In this chapter a brief review is given of computational systems that are motivated by information processing in the brain, an area that is often... Sample PDF
Continuous Attractor Neural Networks
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