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Finding Diverse Examples Using Genetic Algorithms

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Part of the Advances in Soft Computing book series (AINSC,volume 9)

Abstract

The problem of finding qualitative examples is an interesting yet little studied machine learning problem. Take a set of objects, O and a set of classes C, where each object fits into one and only one class. Represent this classification by a total function f: O C. We assume that ∣range(f)∣ « ∣O∣.

Keywords

  • Test Problem
  • Random String
  • Royal Road
  • Traditional Genetic Algorithm
  • Multimodal Optimization

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.

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References

  • Adams, C. A. (1994). The knot book. W.H. Freeman.

    Google Scholar 

  • Attwood, T., and Parry-Smith, D. (1999). Introduction to bioinformatics. Addison Wesley Longman.

    Google Scholar 

  • Bäck, T. (1996). Evolutionary algorithms in theory and practice. Oxford University Press.

    Google Scholar 

  • Belew, R. K. (2000). Finding out about: information retrieval and other technologies for seeking knowledge. Cambridge University Press. (In preparation)

    Google Scholar 

  • Bentley, P. J. (Ed.). (1999). Evolutionary design by computers. Academic Press.

    Google Scholar 

  • Boden, M. (1990). The creative mind: Myths and mechanisms. Abacus.

    Google Scholar 

  • De Jong, K. (1993). Genetic algorithms are NOT function optimizers. In L. Whitley (Ed.), Foundations of genetic algorithms 2 (pp. 5–17). Morgan Kauffmann

    Google Scholar 

  • Goldberg, D. E. (1987). Simple genetic algorithms and the minimal deceptive problem. In L. D. Davis (Ed.), Genetic algorithms and simulated annealing. Morgan Kaufmann.

    Google Scholar 

  • Harvey, I. (1997). Cognition is not computation: Evolution is not optimisation. In W. Gerstner, A. Germond, M. Hasler,, and J.-D. Nicoud (Eds.), Proceedings of the seventh international conference on artificial neural networks (pp. 685–690). Springer-Verlag.

    Google Scholar 

  • Holland, J. H. (1975). Adaptation in natural and artificial systems. MIT Press. (Second edition 1992)

    Google Scholar 

  • Hoste, J., Thistlethwaite, M., and Weeks, J. (1998). The first 1,701,936 knots. The Mathematical Intelligencer, 20(4), 33–48.

    Google Scholar 

  • Johnson, C. G. (2000). Understanding complex systems through examples: a framework for qualitative example finding. In P. A. Gelepithis (Ed.), Complex intelligent systems. Kingston University.

    Google Scholar 

  • Mafoud, S. W. (1997). Niching methods. In T. Bäck, D. B. Fogel, and Z. Michalewicz (Eds.), Handbook of evolutionary computation (pp. C6.1.1—C6.1.4). Oxford University Press/Institute of Physics.

    Google Scholar 

  • Mitchell, M. (1996). An introduction to genetic algorithms. Bradford Books/MIT Press.

    Google Scholar 

  • Mitchell, M., Forrest, S., and Holland, J. (1992). The royal road for genetic algorithms: Fitness landscapes and GA performance. In F. Varela and P. Bourgine (Eds.), Towards a practice of autonomous systems: Proceedings of the first european conference on artificial life. MIT Press. Murasugi, K. (1996). Knot theory and its applications. Birkhäuser.

    Google Scholar 

  • Partridge, D., and Rowe, J. (1994). Computers and creativity. Intellect Books. van Rijsbergen, C. J. (1979). Information retrieval. London: Butterworths.

    Google Scholar 

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© 2001 Springer-Verlag Berlin Heidelberg

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Johnson, C.G. (2001). Finding Diverse Examples Using Genetic Algorithms. In: John, R., Birkenhead, R. (eds) Developments in Soft Computing. Advances in Soft Computing, vol 9. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1829-1_11

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  • DOI: https://doi.org/10.1007/978-3-7908-1829-1_11

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1361-6

  • Online ISBN: 978-3-7908-1829-1

  • eBook Packages: Springer Book Archive