Combining incrementally evolved neural networks based on cellular automata for complex adaptive behaviors

Geum Beom Song, Sung Bae Cho

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

3 Citations (Scopus)

Abstract

There has been extensive work to construct an optimal controller for a mobile robot by evolutionary approaches such as genetic algorithm, genetic programming, and so on. However, evolutionary approaches have a difficulty to obtain the controller for complex and general behaviors. In order to overcome this shortcoming, we propose an incremental evolution method for neural networks based on cellular automata (CA) and a method of combining several evolved modules by a rule-based approach. The incremental evolution method evolves the neural network by starting with simpler environment needed simple behavior and gradually making it more complex and general for complex behaviors. The multimodules integration method can make complex and general behaviors by combining several modules evolved or programmed to do simple behavior. Experimental results show the potential of the incremental evolution and multi-modules integration methods as techniques to make the evolved neural network to do complex and general behaviors.

Original languageEnglish
Title of host publicationProceedings of the 1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks
EditorsDavid B. Fogel, Xin Yao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-129
Number of pages9
ISBN (Electronic)0780365720, 9780780365728
DOIs
Publication statusPublished - 2000 Jan 1
Event1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks, ECNN 2000 - San Antonio, United States
Duration: 2000 May 112000 May 13

Publication series

NameProceedings of the 1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks

Other

Other1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks, ECNN 2000
CountryUnited States
CitySan Antonio
Period00/5/1100/5/13

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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  • Cite this

    Song, G. B., & Cho, S. B. (2000). Combining incrementally evolved neural networks based on cellular automata for complex adaptive behaviors. In D. B. Fogel, & X. Yao (Eds.), Proceedings of the 1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (pp. 121-129). [886227] (Proceedings of the 1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECNN.2000.886227