Evoluční algoritmy pro strukturální učení neuronových sítí

Designing neural networks topologies is s complicated problem when we consider general network structures. Evolutionary algorithm can provide us with interesting solutions of this problem. This work introduces an evolutionary algorithm for evolving neural networks. One of the possible algorithms for...

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Bibliographic Details
Main Author: Kasík, Pavel
Other Authors: Neruda, Roman
Format: Dissertation
Language:English
Published: 2010
Online Access:http://www.nusl.cz/ntk/nusl-298681
Description
Summary:Designing neural networks topologies is s complicated problem when we consider general network structures. Evolutionary algorithm can provide us with interesting solutions of this problem. This work introduces an evolutionary algorithm for evolving neural networks. One of the possible algorithms for evolving neural networks is the NEAT algorithm. The goal of this work is to modify and enhance abilities of the NEAT algorithm. Improvements are focused on utilizing position of a neuron in network, improving crossover procedure and introducing solution of algorithm parallelization that preserve abilities of both NEAT and the new algorithm.