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Evolutionary fuzzy system for architecture control in a constructive neural network
Department of Computer Science and Statistics, University of São Paulo, Sao Carlos - SP, Brazil.
Department of Computer Science, State University of Maringa, Maringa - PR, Brazil.
Halmstad University, School of Information Technology.
2005 (English)In: Proceedings 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation: CIRA 2005. June 27-30, 2005. Espoo, Finland, New York, NY: Institute of Electrical and Electronics Engineers (IEEE), 2005, p. 541-546Conference paper, Published paper (Refereed)
Abstract [en]

This work describes an evolutionary system to control the growth of a constructive neural network for autonomous navigation. A classifier system generates Takagi-Sugeno fuzzy rules and controls the architecture of a constructive neural network. The performance of the mobile robot guides the evolutionary learning mechanism. Experiments show the efficiency of the classifier fuzzy system for analyzing if it is worth inserting a new neuron into the architecture. ©2005 IEEE.

Place, publisher, year, edition, pages
New York, NY: Institute of Electrical and Electronics Engineers (IEEE), 2005. p. 541-546
Keywords [en]
constructive neural networks, classifier systems, robot navigation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:hh:diva-40855DOI: 10.1109/CIRA.2005.1554333ISI: 000231588200090Scopus ID: 2-s2.0-28444444449ISBN: 0-7803-9355-4 (print)OAI: oai:DiVA.org:hh-40855DiVA, id: diva2:1392770
Conference
IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA 2005), Espoo, Finland, June 27-30, 2005
Available from: 2020-02-10 Created: 2020-02-10 Last updated: 2020-03-10Bibliographically approved

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Antonelo, Eric Aislan

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf