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European Conference on Genetic Programming

EuroGP 2005: Genetic Programming pp 108–119Cite as

Genetic Transposition in Tree-Adjoining Grammar Guided Genetic Programming: The Duplication Operator

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

Abstract

We empirically investigate the use of dual duplication/truncation operators both as mutation operators and as generic local search operators, in combination with genetic search in a tree adjoining grammar guided genetic programming system (TAG3P). The results show that, on the problems tried, duplication/truncation works well as a mutation operator but not reliably when the complexity of the problem was scaled up. When using these dual operators as a generic local search operator, however, it helped TAG3P not only to solve the problems reliably but also cope well with scalability in problem complexity. Moreover, it managed to solve problems with very small population sizes.

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References

  1. Aarts, E., Lenstra, J.K.: Local Search in Combinatorial Optimization. John Wiley and Sons, Chichester (1997)

    MATH  Google Scholar 

  2. Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetic Programming: An Introduction. Morgan Kaufmann Pub., San Francisco (1998)

    MATH  Google Scholar 

  3. Drlica, K.: Understanding DNA and Gene Cloning: A Guide for the Curious. John Wiley & Sons. USA (1984)

    Google Scholar 

  4. Ferreira, C.: Gene Expression Programming: A New Adaptive Algorithm for Solving Problems. Complex Systems 3(2), 87–129 (2001)

    Google Scholar 

  5. Ferreira, C.: Mutation, Transposition, and Recombination: An Analysis of the Evolutionary Dynamics. In: Proceedings of the 4th Int. Workshop on Frontiers in Evolutionary Algorithms, pp. 614–617 (2002)

    Google Scholar 

  6. Geyer-Schulz, A.: Fuzzy Rule-Based Expert Systems and Genetic Machine Learning. Physica-Verlag, Heidelberg (1995)

    Google Scholar 

  7. Gruau, F.: On Using Syntactic Constraints with Genetic Programming. In: Advances in Genetic Programming II, pp. 377–394. MIT Press, Cambridge (1996)

    Google Scholar 

  8. Haynes, T.: Duplication of Coding Segments in Genetic Programming, Technical Report UTULSA-MCS-96-03, The University of Tulsa (1996)

    Google Scholar 

  9. Haynes, T.: Collective Adaptation: The Exchange of Coding Segments. Evolutionary Computation 6(4), 311–338 (1998)

    Article  Google Scholar 

  10. Haynes, T.: Collective Adaptation: The Sharing of Building Blocks, PhD Thesis, Department of Mathematical and Computer Sciences, University of Tulsa (1998)

    Google Scholar 

  11. Holland, J.: Adaptation in Natural and Artificial Intelligence: An Introductory Analysis with Application in Biology, Control, and Artificial Intelligence. Michigan University Press (1975)

    Google Scholar 

  12. Joshi, A.K., Levy, L.S., Takahashi, M.: Tree Adjunct Grammars. Journal of Computer and System Sciences 10(1), 136–163 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  13. Joshi, A.K., Schabes, Y.: Tree Adjoining Grammars. In: Handbook of Formal Languages, pp. 69–123. Springer, Heidelberg (1997)

    Google Scholar 

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

    MATH  Google Scholar 

  15. Koza, J.: Genetic Programming II: Automatic Discoveries of Reusable Programs. MIT Press, Cambridge (1994)

    Google Scholar 

  16. Koza, J., Andre, D., Bennett III, F.H., Kean, M.: Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann, San Francisco (1999)

    MATH  Google Scholar 

  17. Koza, J.: Gene Duplication to Enable Genetic Programming to Concurrently Evolve Both the Architecture and Work-Performing Steps of a Computer Program. In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pp. 734–740 (1995)

    Google Scholar 

  18. Koza, J., Andre, D.: Classifying Protein Segments as Transmembrane Domains Using Architecture-Altering Operations in Genetic Programming. In: Advances in Genetic Programming 2, ch. 8. MIT Press, Cambridge (1996)

    Google Scholar 

  19. Lin, S., Kerninghan, B.W.: An Effective Heuristic Algorithm for the Traveling Salesman Problem. Operation Research 21, 458–516 (1973)

    Article  Google Scholar 

  20. Hoai, N.X., McKay, R.I., Abbass, H.A.: Tree Adjoining Grammars, Language Bias, and Genetic Programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003, vol. 2610, pp. 335–344. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  21. Hoai, N.X., McKay, R.I.: Softening the Structural Difficulty with TAG-based Representation and Insertion/Deletion Operators. In: Deb, K., et al. (eds.) GECCO 2004, vol. 3103, pp. 605–616. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  22. Hoai, N.X., McKay, R.I.: An Investigation on the Roles of Insertion and Deletion Operators in Tree Adjoining Grammar Guided Genetic Programming. In: Proceedings of Congress on Evolutionary Computation (CEC 2004), pp. 472–477. IEEE Press, Los Alamitos (2004)

    Chapter  Google Scholar 

  23. Hoai, N.X., McKay, R.I., Essam, D.: Genetic Transposition in Tree-Adjoining Grammar Guided Gentic Programming: The Relocation Operator. In: Proceedings of the 5 th International Conference on Simulated Evolution and Learning (SEAL 2004). IEEE Press, Los Alamitos (2004)

    Google Scholar 

  24. Hoai, N.X., McKay, R.I., Essam, D.: Solving Symbolic Regression Problem with Tree Adjoining Grammar Guided Genetic Programming. Australian Journal of Inteligent Information Processing Systems 7(3), 114–121 (2002)

    Google Scholar 

  25. Ohno, S.: Evolution by Duplication. Springer, Heidelberg (1970)

    Google Scholar 

  26. Schwefel, H.P.: Projekt MHD-Staustrahlrohr: Experimentelle Optimierung einer Zweiphasenduse Teil I Technischer Bericht 11.034/68, 35, AEG Forschungsinstitut, Berlin (1968)

    Google Scholar 

  27. O’Neil, M., Ryan, C.: Grammatical Evolution. IEEE Trans on EC 4(4), 349–357 (2000)

    Google Scholar 

  28. Ridley, M.: Evolution, 2nd edn. Blackwell Science, USA (1996)

    Google Scholar 

  29. Whigham, P.A.: Grammatical Bias for Evolutionary Learning, Ph.D Thesis, UNSW, Australia (1996)

    Google Scholar 

  30. Wong, M.L., Leung, K.S.: Evolutionary Program Induction Directed by Logic Grammars. Evolutionary Computation 5, 143–180 (1997)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of IT&EE, Australian Defence Force Academy, University of New South Wales, ACT 2600, Australia

    Nguyen Xuan Hoai, Robert Ian Bob McKay, Daryl Essam & Hoang Tuan Hao

Authors
  1. Nguyen Xuan Hoai
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  2. Robert Ian Bob McKay
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  3. Daryl Essam
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  4. Hoang Tuan Hao
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Editor information

Editors and Affiliations

  1. No Affiliation,  

    Maarten Keijzer

  2. Dipartimento di Tecnologie dell’Informazione, Università di Milano Crema,  

    Andrea Tettamanzi

  3. Université Louis Pasteur, LSIIT, FDBT, Pôle API, F-67400, Illkirch, France

    Pierre Collet

  4. National e-Science Centre, University of Edinburgh, United Kingdom

    Jano van Hemert

  5. Institut des Systèmes d’Information (ISI), Université de Lausanne, Hautes Etudes Commerciales (HEC),  

    Marco Tomassini

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© 2005 Springer-Verlag Berlin Heidelberg

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Hoai, N.X., McKay, R.I.B., Essam, D., Hao, H.T. (2005). Genetic Transposition in Tree-Adjoining Grammar Guided Genetic Programming: The Duplication Operator. 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_10

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  • DOI: https://doi.org/10.1007/978-3-540-31989-4_10

  • 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)

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