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Multi-Agent Environment for Hybrid AI Models

  • Conference paper
Artificial Neural Nets and Genetic Algorithms

Abstract

We describe a system which represents hybrid computational models as communities of cooperating autonomous software agents. It supports easy creation of combinations of modern artificial intelligence methods, namely neural networks, genetic algorithms and fuzzy logic controllers, and their distributed deployment over a cluster of workstations. The adaptive agents paradigm allows for semiautomated model generation, or even evolution of hybrid schemes.

This work has been partially supported by the Grant Agency of the Czech Republic under grants no. 201/00/1489 and 201/99/P057.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Academy of Sciences of the Czech Republic, P.O. Box 5, 18207, Prague, Czech Republic

    Zuzana Petrová

Authors
  1. Roman Neruda
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  2. Pavel Krušina
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  3. Zuzana Petrová
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Czech Republic

    Věra Kůrková  & Roman Neruda  & 

  2. Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic

    Miroslav Kárný

  3. Division of Mathematics, School of Mathematical and Information Sciences Coventry University, Coventry, UK

    Nigel C. Steele

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© 2001 Springer-Verlag Wien

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Neruda, R., Krušina, P., Petrová, Z. (2001). Multi-Agent Environment for Hybrid AI Models. In: Kůrková, V., Neruda, R., Kárný, M., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6230-9_89

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  • DOI: https://doi.org/10.1007/978-3-7091-6230-9_89

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83651-4

  • Online ISBN: 978-3-7091-6230-9

  • eBook Packages: Springer Book Archive

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