A Developmental Model for the Evolution of Artificial Neural Networks

Author:

Astor J. C.1,Adami C.1

Affiliation:

1. Computation and Neural Systems and Kellogg Radiation Laboratory California Institute of Technology Pasadena, CA 91125, USA

Abstract

We present a model of decentralized growth and development for artificial neural networks (ANNs), inspired by developmental biology and the physiology of nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates. The chemicals and substrates, in turn, are modeled by a simple artificial chemistry. While the system is designed to allow for the evolution of complex networks, we demonstrate the power of the artificial chemistry by analyzing engineered (handwritten) genomes that lead to the growth of simple networks with behaviors known from physiology. To evolve more complex structures, a Java-based, platform-independent, asynchronous, distributed genetic algorithm (GA) has been implemented that allows users to participate in evolutionary experiments via the World Wide Web.

Publisher

MIT Press - Journals

Subject

Artificial Intelligence,General Biochemistry, Genetics and Molecular Biology

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