Skip to main content

The Fighter Aircraft LCS: A Case of Different LCS Goals and Techniques

  • Conference paper
  • First Online:
Learning Classifier Systems (IWLCS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1813))

Included in the following conference series:

Abstract

A system employed by the authors to acquire novel fighter aircraft manoeuvres from combat simulation is more akin to the traditional LCS model than to more recent systems. Given the difficulties often experienced in LCS research on simple problems, one must ask how a relatively primitive LCS has had consistent success in the complex domain of fighter aircraft manoeuvring. This paper presents the fighter aircraft LCS, in greater detail than in previous publications. Positive results from the system are discussed. The paper then focuses on the primary reasons the fighter aircraft LCS has avoided the difficulties of the traditional LCS. The authors believe the system’s success has three primary origins: differences in credit assignment, differences in action encoding, and (possibly most importantly) a difference in system goals. In the fighter aircraft system, the goal has been simply the discovery of innovative, novel tactics, rather than online control. The paper concludes by discussing the most salient features of the fighter aircraft learning system, and how those features may be profitably combined with other LCS developments.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Booker, L. B. (1992) Viewing Classifier Systems as an Integrated Architecture. Paper presented at The First International Conference on Learning Classifier Systems, Houston, Texas, October 1.

    Google Scholar 

  2. Goldberg, D. E. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.

    Google Scholar 

  3. Grefenstette, J. J. (1988) Credit assignment in rule discovery systems based on genetic algorithms. Machine Learning 3. pp. 225–246.

    Google Scholar 

  4. Holland, J. H. (1992) Adaptation in Natural and Artificial Systems MIT Press.

    Google Scholar 

  5. Holland, J. H., Holyoak, K. J., Nisbett, R. E. and Thagard, P. R. (1986) Induction: Processes of inference, learning, and discovery. MIT Press, Cambridge, MA.

    Google Scholar 

  6. Holland, J. H. and Reitman, J. S. (1978) Cognitive systems based on adaptive algorithms. In Waterman, D. A. and Hayes-Roth, F., “ Pattern directed inference systems”. Academic Press, NY.

    Google Scholar 

  7. Shaw, R. L. (1998) Fighter Combat: Tactics and Maneuvering. United States Naval Institute Press.

    Google Scholar 

  8. Smith, R. E. and Dike B. A. (1995) Learning novel fighter combat maneuver rules via genetic algorithms. International Journal of Expert Systems, 8(3) (1995) 247–276.

    Google Scholar 

  9. Smith, R. E., Dike, B. A. and Stegmann, S. A. (1994) Inheritance in Genetic Algorithms, in: Proceedings of the ACM 1995 Symposium on Applied Computing. ACM Press. pp. 345–350.

    Google Scholar 

  10. Smith, R. E., Dike, B. A., Mehra, R. K., Ravichandran, B. and El-Fallah, A. (in press). Classifier Systems In Combat: Two-Sided Learning of Maneuvers For Advanced Fighter Aircraft. Computer Methods in Applied Mechanics and Engineering, Elsevier.

    Google Scholar 

  11. Sutton, R. S. and Barto, A. G. (1998) Reinforcement Learning: An Introduction. MIT Press.

    Google Scholar 

  12. Watkins, J. C. H. (1989). Learning with delayed rewards. Unpublished doctoral dissertation. King’s College, London.

    Google Scholar 

  13. Wilson, S. W. (1994) ZCS: A zeroth-level classifier system, Evolutionary Computation 2(1). pp. 1–18.

    Article  Google Scholar 

  14. Wilson, S. W. (1995). Classifier fitness based on accuracy. Evolutionary Computation, 3(1), 149–176.

    Article  Google Scholar 

  15. Wilson, S. W. (1999) State of XCS Classifier System Research. Technical Report Number 99.1.1 (Unpublished), Prediction Dynamics, Concord, MA.

    Google Scholar 

  16. P. M. Doane, C. H. Gay and J. A. Fligg, Multi-system integrated control (MuSIC) program. final report. Technical report, Wright Laboratories, Wright-Patterson AFB, OH., 1989.

    Google Scholar 

  17. R. Axelrod, The Evolution of Cooperation. (Basic Books, New York, 1984)

    Google Scholar 

  18. R. D. Luce and H. Raiffa, Games and Decisions. (Dover Publications, 1989).

    Google Scholar 

  19. D. Floriano and S. Nolfi, S., God save the red queen!: Competition in co-evolutionary robotics, in: Proceedings of the Second International Conference on Genetic Programming, (1997) 398–406.

    Google Scholar 

  20. Smith, R. E., Memory Exploitation in Learning Classifier Systems,(1995) Evolutionary Computation, 2(3), pp. 199–220

    Article  Google Scholar 

  21. Wilson, S. W. (1994) ZCS: A zeroth-level classifier system, Evolutionary Computation 2(1). pp. 1–18.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Smith, R.E., Dike, B.A., Ravichandran, B., El-Fallah, A., Mehra, R.K. (2000). The Fighter Aircraft LCS: A Case of Different LCS Goals and Techniques. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS 1999. Lecture Notes in Computer Science(), vol 1813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45027-0_15

Download citation

  • DOI: https://doi.org/10.1007/3-540-45027-0_15

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67729-1

  • Online ISBN: 978-3-540-45027-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics