Hybrid programming environments

  • Philip C. Treleaven
  • Paulo V. Rocha
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 686)


Following the emergence of each new “Intelligent” computing technology — expert systems, fuzzy logic, neural networks and genetic algorithms — sophisticated programming environments have been developed to assist application building. Each environment being dedicated to a single intelligent technology. These environments can be classified as: application-oriented — dedicated to a specific application domain; algorithm-oriented — supporting a single algorithm; or general-purpose — comprehensive tool kits for any domain.

However, hybrid applications are now being build combining a number of intelligent techniques. Thus hybrid programming environments are required that allow combination of neural networks and genetic algorithms. This paper briefly reviews programming environments for neural networks, genetic algorithms and hybrid systems, using three of UCL's Esprit projects: Galatea, Papagena and Hansa as case studies.


Neural Network Genetic Algorithm Virtual Machine Hybrid System Programming Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Philip C. Treleaven
    • 1
  • Paulo V. Rocha
    • 1
  1. 1.Department of Computer ScienceUniversity College LondonLondonUK

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