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Genetic programming artificial nervous systems artificial embryos and embryological electronics

  • Hugo de Garis
Genetic Algorithms Genetic Programming
Part of the Lecture Notes in Computer Science book series (LNCS, volume 496)

Abstract

This paper shows that it is possible to build hyper-complex systems such as an artificial nervous system or an artificial embryo, despite the fact that their interactions or dynamics are (probably) too complicated to be analyzed. Genetic Programming (GP) is "applied evolution", i.e. using the Genetic Algorithm (GA) [GOLDBERG 1989] to evolve hyper-complex systems. Future work using the GP paradigm will probably lead to electronic circuits being "grown" in (and having their functionality tested in) special hardware called "Darwin Machines", thus creating a new field called "Embryonics" (i.e. Embryological Electronics).

Keywords

Genetic Programming Genetic Algorithm Hyper-Complex Systems Time Dependent Neural Network Modules GenNets Brain Building Artificial Nervous Systems Genetically Programmed Insect Robots Artificial Embryos Artificial Life Embryonics Darwin Machines 

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References

  1. [de GARIS 1990]
    "Genetic Programming: Building Artificial Nervous Systems Using Genetically Programmed Neural Network Moduels", Proceedings 7th. Int. Conf. on Machine Learning, Austin Texas, June 1990, Morgan Kaufmann, 1990.Google Scholar
  2. [de GARIS 1991]
    "Genetic Programming", Chapter 15, in book, "Neural and Intelligent Systems Integration", ed. Prof. Branko Soucek, WILEY, 1991.Google Scholar
  3. [GOLDBERG 1989]
    “Genetic Algorithms in Search, Optimization, and Machine Learning”, D.E. Goldberg, Addison-Wesley, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Hugo de Garis
    • 1
    • 2
  1. 1.CADEPS Artificial Intelligence and Artificial Life Research UnitUniversite Libre de Bruxelles (U.L.B.)BrusselsBelgium, Europe
  2. 2.Center for Artificial IntelligenceGeorge Mason UniversityVirginiaUSA

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