Grammatical development of evolutionary modular neural networks?

Sung Bae Cho, Katsunori Shimohara

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Evolutionary algorithms have shown a great potential to develop the optimal neural networks that can change the architectures and learning rules according to the environments. In order to boost up the scalability and utilization, grammatical development has been considered as a promising encoding scheme of the network architecture in the evolutionary process. This paper presents a preliminary result to apply a grammatical development method called L-system to determine the structure of a modular neural network that was previously proposed by the authors. Simulation result with the recognition problem of handwrit- ten digits indicates that the evolved neural network has reproduced some of the characteristics of natural visual system, such as the organization of coarse and fine processing of stimuli in separate pathways.

Original languageEnglish
Title of host publicationSimulated Evolution and Learning - 2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998, Selected Papers
EditorsBob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, Takeshi Furuhashi
PublisherSpringer Verlag
Number of pages8
ISBN (Print)3540659072, 9783540659075
Publication statusPublished - 1999
Event2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998 - Canberra, Australia
Duration: 1998 Nov 241998 Nov 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1999.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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