Skip to main content

Evolving Defence Strategies by Genetic Programming

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3447))

Abstract

Computer games and simulations are commonly used as a basis for analysing and developing battlefield strategies. Such strategies are usually programmed explicitly, but it is also possible to generate them automatically via the use of evolutionary programming techniques. We focus in particular on the use of genetic programming to evolve strategies for a single defender facing multiple simultaneous attacks. By expressing the problem domain in the form of a ‘Space Invaders’ game, we show that it is possible to evolve winning strategies for an increasingly complex sequence of scenarios.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Laird, J.E.: Research in Human-Level AI Using Computer Games. Communications of the ACM 45(1), 32–35 (2002)

    Article  Google Scholar 

  2. Gross, R., Albrecht, K., Kantschik, W., Banzhaf, W.: Evolving Chess Playing Programs. In: Langdon, W.B., et al. (eds.) GECCO 2002, pp. 740–747. Morgan Kaufmann, San Francisco (2002)

    Google Scholar 

  3. Chellapilla, K., Fogel, D.B.: Evolving an Expert Checkers Playing Program without Using Human Expertise. IEEE Trans. on Evolutionary Computation 5(4), 422–428 (2001)

    Article  Google Scholar 

  4. Kendall, G., Willdig, M.: An Investigation of an Adaptive Poker Player. In: Stumptner, M., Corbett, D.R., Brooks, M. (eds.) Canadian AI 2001. LNCS (LNAI), vol. 2256, pp. 189–200. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  5. Eskin, E., Siegel, E.V.: Genetic Programming Applied to Othello: Introducing Students to Machine Learning Research. In: Proc. 30th Technical Symposium of the ACM Special Interest Group in Computer Science Education (SIGCSE), New Orleans, LA, USA, pp. 242–246 (1999)

    Google Scholar 

  6. Pollack, J., Blair, A.D., Land, M.: Coevolution of a Backgammon Player. In: Langton, C.G., Shimohara, K. (eds.) Artificial Life V: Proc. 5th Int. Workshop on the Synthesis and Simulation of Living Systems, pp. 92–98. MIT Press, Cambridge (1996)

    Google Scholar 

  7. Koza, J.R.: Genetic Evolution and Co-Evolution of Game Strategies. In: International Conf. on Game Theory and its Applications, Stony Brook, New York (1992)

    Google Scholar 

  8. Miles, C., Louis, S.J., Cole, N.: Learning to Play Like a Human: Case Injected Genetic Algorithms Applied to Strategic Computer Game Playing. In: Congress on Evolutionary Computation (CEC 2004), Portland, Oregon, USA (2004)

    Google Scholar 

  9. Moore, F.W., Garcia, O.N.: A Genetic Programming Approach to Strategy Optimization in the Extended Two-Dimensional Pursuer/Evader Problem. In: Koza, J.R., et al. (eds.) Genetic Programming 1997: Proceedings of the Second Annual Conference, pp. 249–254. Morgan Kaufmann, San Francisco (1997)

    Google Scholar 

  10. Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

  11. Moore, F.W.: A Methodology for Missile Countermeasures Optimization under Uncertainty. Evolutionary Computation 10(2), 129–149 (2002)

    Article  Google Scholar 

  12. Nyongesa, H.O.: Generation of Time-Delay Algorithms for Anti-air Missiles using Genetic Programming. In: Boers, E.J.W., Gottlieb, J., Lanzi, P.L., Smith, R.E., Cagnoni, S., Hart, E., Raidl, G.R., Tijink, H. (eds.) EvoIASP 2001, EvoWorkshops 2001, EvoFlight 2001, EvoSTIM 2001, EvoCOP 2001, and EvoLearn 2001. LNCS, vol. 2037, pp. 243–247. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  13. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jackson, D. (2005). Evolving Defence Strategies by Genetic Programming. In: Keijzer, M., Tettamanzi, A., Collet, P., van Hemert, J., Tomassini, M. (eds) Genetic Programming. EuroGP 2005. Lecture Notes in Computer Science, vol 3447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31989-4_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-31989-4_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25436-2

  • Online ISBN: 978-3-540-31989-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics