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A Competitive Building Block Hypothesis

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Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

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Abstract

This paper is concerned with examining the way in which rooted building blocks grow in GP-like systems. We hypothesize that, in addition to the normal notion of co-operative building blocks, there are also competitive building blocks in the population. These competitive building blocks are all of the rooted variety, all share a similar root structure and compete with each other to spread their particular extensions to the common structure throughout the population. We demonstrate that not only do these competitive building blocks exist, but that they work in tandem with non-rooted co-operative building blocks.

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References

  1. Angeline, P.J., Pollack, J.B.: Competitive environments evolve better solutions for complex tasks. In: Forrest, S. (ed.) Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-1993, University of Illinois at Urbana-Champaign, July 17-21, pp. 264–270. Morgan Kaufmann, San Francisco (1993)

    Google Scholar 

  2. Goldberg, D.E.: Simple genetic algorithms and the minimal, deceptive problem. In: Davis, L. (ed.) Genetic Algorithms and Simulated Annealing, pp. 74–88. Morgan Kaufmann, San Francisco (1987)

    Google Scholar 

  3. Goldberg, D.E.: Genetic algorithms and walsh functions: part i, a gentle introduction. Complex Systems 3(2), 129–152 (1989)

    MATH  MathSciNet  Google Scholar 

  4. Goldberg, D.E.: The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, Dordrecht (2002)

    MATH  Google Scholar 

  5. Holland, J.H.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Harbor (1975)

    Google Scholar 

  6. Keijzer, M.: Scientific Discovery using Genetic Programming. PhD thesis, Danish Technical University, Lyngby, Denmark (March 2002)

    Google Scholar 

  7. Keijzer, M., Ryan, C., O’Neill, M., Cattolico, M., Babovic, V.: Ripple crossover in genetic programming. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, pp. 74–86. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. Langdon, W.B., Poli, R.: Foundations of Genetic Programming. Springer, Heidelberg (2002)

    MATH  Google Scholar 

  9. McPhee, N.F., Hopper, N.J.: Analysis of genetic diversity through population history. In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honavar, V., Jakiela, M., Smith, R.E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference, Orlando, Florida, USA, July 13-17, vol. 2, pp. 1112–1120. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  10. Mitchell, M., Forrest, S., Holland, J.H.: The royal road for genetic algorithms: Fitness landscapes and GA performance. In: Varela, F.J., Bourgine, P. (eds.) Towards a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life, Paris, pp. 245–254. A Bradford book, The MIT Press, Cambridge (1991)

    Google Scholar 

  11. O’Neill, M., Ryan, C.: Crossover in grammatical evolution: A smooth operator? In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds.) EuroGP 2000. LNCS, vol. 1802, pp. 149–162. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  12. O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in a Arbitrary Language. Genetic programming, vol. 4. Kluwer Academic Publishers, Dordrecht (2003)

    MATH  Google Scholar 

  13. O’Neill, M., Ryan, C., Keijzer, M., Cattolico, M.: Crossover in grammatical evolution. Genetic Programming and Evolvable Machines 4(1), 67–93 (2003)

    Article  MATH  Google Scholar 

  14. O’Reilly, U.-M., Oppacher, F.: The troubling aspects of a building block hypothesis for genetic programming. In: Darrell Whitley, L., Vose, M.D. (eds.) Foundations of Genetic Algorithms 3, Estes Park, Colorado, USA, July 31–August 2, 1994, pp. 73–88. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

  15. O’Sullivan, J., Ryan, C.: An investigation into the use of different search strategies with grammatical evolution. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 268–277. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  16. Ryan, C., Collins, J.J., Neill, M.O.: Grammatical evolution: Evolving programs for an arbitrary language. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391, pp. 83–95. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  17. Ryan, C., Keijzer, M., Nicolau, M.: On the avoidance of fruitless wraps in grammatical evolution. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2724, pp. 1752–1763. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  18. Ryan, C., Nicolau, M.: Doing genetic algorithms the genetic programming way. In: Riolo, R.L., Worzel, B. (eds.) Genetic Programming Theory and Practise, ch. 12, pp. 189–204. Kluwer, Dordrecht (2003)

    Google Scholar 

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Ryan, C., Majeed, H., Azad, A. (2004). A Competitive Building Block Hypothesis. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_73

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

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