Advertisement

Phase transition networks: A modelling technique supporting the evolution of autonomous agents' tactical and operational activities

  • Anthony G. Deakin
  • Derek F. Yates
Novel Techniques and Applications of Evolutionary Algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1305)

Abstract

The purpose of this paper is to introduce a modelling technique which the authors are using to evolve autonomous agents' action plans by means of genetic programming operations. The technique is described and its application is illustrated through examples. A brief outline is given of a formal model construction methodology that has been developed to accompany the modelling technique. Finally, the features of the technique are reviewed. Particular note is made of its suitability for modelling a broad variety of artificial and natural systems for problem-solving and domain exploration by means of evolutionary computation.

Keywords

Genetic Programming Phase Transfer Autonomous Agent Traffic Light Blood Glucose Regulation 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bench-Capon, T. J. M.: Knowledge representation. San Diego, CA: Academic Press (1990)Google Scholar
  2. 2.
    Dartnall, T.: Review of Peterson, D. (Ed.): Forms of representation: an interdisciplinary theme for cognitive science. Intellect Books (1996) in AISB Quarterly 97 (1997) 8–9Google Scholar
  3. 3.
    Deakin, A. G., Yates, D. F.: Genetic programming tools available on the web: a first encounter. In GP-96, Koza, John R., Goldberg, David E., Fogel, David B., and Riolo, Rick L. (editors): Genetic Programming 1996: Proceedings of the First Annual Conference, July 28–31, 1996, Stanford University. Cambridge, MA: The MIT Press (1996) 420Google Scholar
  4. 4.
    Jones, D.: Blood glucose regulation. Honours project report. Department of Computer Science, the University of Liverpool (1992)Google Scholar
  5. 5.
    Koza, J. R.: Genetic programming: on the programming of computers by means of natural selection. Cambridge, MA: The MIT Press (1992)Google Scholar
  6. 6.
    Paton, R. C.: Understanding biosystem organisation-part 1: techniques. International Journal of Science Education 15 (1993)Google Scholar
  7. 7.
    Peterson, D.: Introduction. In Peterson, D. (Ed.): Forms of representation: an interdisciplinary theme for cognitive science. Intellect Books (1996)Google Scholar
  8. 8.
    Sloman, A.: Towards a general theory of representations. In Peterson, D. (Ed.): Forms of representation: an interdisciplinary theme for cognitive science. Intellect Books (1996)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Anthony G. Deakin
    • 1
  • Derek F. Yates
    • 1
  1. 1.Department of Computer ScienceThe University of LiverpoolLiverpool

Personalised recommendations