Self-Organization, Evolution, and Neural Networks

  • Friedhelm Mündemann
Conference paper
Part of the Informatik-Fachberichte book series (INFORMATIK, volume 304)

Abstract

Neural networks characterize a field of computer science that goes through a renaissance after a long period of sleep of about some 30 years and is developing rapidly today. Some very promising results achieved show that neural networks may go beyond solutions known so far.

This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literature

  1. Ablay, P.: Optimieren mit Evolutionsstralegien, Spektrum der Wissenschaft, Juli 1987, p. 104–115Google Scholar
  2. Ayala, F.J.: Mechanismen der Evolution, Spektrum der Wissenschaft, Mai 1979, p. 8 - 18Google Scholar
  3. Babb 11, R.G.: Parallel Processing with Large-Grain Data Flow Techniques, IEEE Computer, July 1984, p. 55–61Google Scholar
  4. Batcson, G.: Ökologie des Geistes, Suhrkamp-Verlag 1984Google Scholar
  5. DARPA Neural Network Study (October 1987-February 1988), AFCEA International PressGoogle Scholar
  6. Dennis, J.B., Misunas, D.P.: A Computer Architecture for Highly Parallel Signal Processing, ACM Proceedings of the 1974 National Conference, New York, Nov. 1974, p. 402–409Google Scholar
  7. Dennis, J.B.: The Varieties of Data Flow Computers, 1th International Conference on Distributed Computing Systems, Huntsvilie/Alabama, Oct. 1979, p. 430–439Google Scholar
  8. Dennis, J.B.: Data Flow Supercomputers, IEEE Computer, Nov.1980, p. 48 - 56Google Scholar
  9. Dennis, J.B., Gao, G.-R., Todd, K.W.: Modeling the Weather with a Data Flow Supercomputer, IEEE Transactions on Computers, Vol.C-33, No. 7, July 1984, p. 592–603Google Scholar
  10. Goldberg, A., Robson, D.,Ingalls, D.: SMALLTALK-80: The Language and its Interpretation SMALLTALK-80: The Interactive Programming Environment, Edison-Wesley, Reading/Mass., 1983Google Scholar
  11. Grefenslctle, J.J., Pcttey, C.: Approaches to Machine Learning with Genetic Algorithms, Proceedings of the 1986 IEEE International Conference on Systems, Man and Cybernetics, Atlanta/Georgia, October 1986, p. 55–60Google Scholar
  12. Hoare, C.A.R.: Communicating Sequential Processes, Communications of the ACM, Vol. 21, Aug. 1978, p. 666–677MATHCrossRefGoogle Scholar
  13. Hull, M.E.: Implementations of the CSP Notation for Concurrent Systems, The Computer Journal, Vol. 29, No. 6, 1986 p. 500–505MATHCrossRefGoogle Scholar
  14. Kimura, M.: Die “neutrale” Theorie der molekularen Evolution, Spektrum der Wissenschaft, Januar 1980, p. 94–102Google Scholar
  15. Linskcr, R.: From basic Network Principles to Neural Architecture, Proc. Natl. Acad. Sei. USA, Vol.83, 3 Parts: Emergence of spatial-opponent cells, p.7508–7512, Emergence of orientation-selective cells, p.8390-8394, Emergence of orientation columns, p.8779–8783Google Scholar
  16. Linsker, R.: Self-Organization in a Perceptual Network, IEEE Computer, March 1988, p. 105–117Google Scholar
  17. Lohmann, R.: Selforganization by Evolution Strategy in Visual Systems, Workshop “Evolutionary Strategies”, UniBwM, April ’89, to appearGoogle Scholar
  18. May, D.: OCCAM, SIGPLAN Notices, Vol. 18, April 1983, S. 69–79CrossRefGoogle Scholar
  19. Mühlenbein, H., Kindermann, J.: The Dynamics of Evolution and Learning-Towards Genetic Neural Networks, Workshop “Evolutionary Strategies”, UniBwM, April ’89, to appearGoogle Scholar
  20. Mündemann, F.: Ein evolutionsbasierter Ansatz zur Konstruktion eines neuronalen Netzes für Mustererkennungsaufgaben, K.Ecker (ed.), Proc. ICoLe ’88, Berichte des Instituts für Informatik der Universität ClausthalGoogle Scholar
  21. Osterloh, M.: Handlungsspielräume und Informationsverarbeitung, Huber 1983Google Scholar
  22. Treleaven, P.C., Brownbridge, D.R., Hopkins, R.P.: Data-Driven and Demand-Driven Computer Architecture, ACM Computing Surveys, Vol.14, Nr. l, March 1982, S. 93–143Google Scholar
  23. Stebbins, G.L., Ayala, F.J.: Die Evolution des Darwinismus, Spektrum der Wissenschaft, Sept. 1985, p. 58–71Google Scholar
  24. Widrow, B., Winter, R.: Neural Nets for Adaptive Filtering and Adaptive Pattern Recognition, IEEE Computer, March 1988, p. 25–39Google Scholar
  25. Zhou, H., Grefenstette, J.J.: Induction of finite automata by genetic algorithms, Proceedings of the 1986 IEEE International Conference on Systems, Man and Cybernetics, Atlanta/Georgia, October 1986, p. 170–174Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Friedhelm Mündemann
    • 1
  1. 1.Faculty of Computer ScienceUniversity of the Federal Armed Forces MunichGermany

Personalised recommendations