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Innovations in ART Neural Networks pp 133–166Cite as

Art-Based Autonomous Learning Systems: Part I — Architectures and Algorithms

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 43))

Abstract

This chapter describes the design of novel ART-based intelligent systems that are able to learn and, at the same time, to refine their knowledge in perpetuity. Fuzzy ARTMAP and the Probabilistic Neural Network are integrated to form a hybrid system that possesses the desirable properties for incremental, causal learning as well as for Bayesian probability estimation. Subsequently, a multiple neural network architecture is devised to aggregate outputs from several individual networks into a unified decision. A number of algorithms is proposed to increase the generalization and adaptability of the resulting systems.

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Author information

Authors and Affiliations

  1. School of Industrial Technology, Universiti Sains Malaysia, 11800, Penang, Malaysia

    C. P. Lim

  2. Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, Sheffield, SI 3JD, UK

    R. F. Harrison

Authors
  1. C. P. Lim
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  2. R. F. Harrison
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Editor information

Editors and Affiliations

  1. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Adelaide, Mawson Lakes, South Australia, 5095

    Lakhmi C. Jain

  2. Dipartimento di Ingegneria della Informazione, University of Pisa, Via Diotisalvi, 2, 56126, Pisa, Italy

    Beatrice Lazzerini

  3. Department of Electrical Engineering, Middle East Technical University, 06531, Ankara, Turkey

    Ugur Halici

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© 2000 Springer-Verlag Berlin Heidelberg

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Lim, C.P., Harrison, R.F. (2000). Art-Based Autonomous Learning Systems: Part I — Architectures and Algorithms. In: Jain, L.C., Lazzerini, B., Halici, U. (eds) Innovations in ART Neural Networks. Studies in Fuzziness and Soft Computing, vol 43. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1857-4_6

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  • DOI: https://doi.org/10.1007/978-3-7908-1857-4_6

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2469-8

  • Online ISBN: 978-3-7908-1857-4

  • eBook Packages: Springer Book Archive

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