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Trivial Geography in Genetic Programming

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Genetic Programming Theory and Practice III

Part of the book series: Genetic Programming ((GPEM,volume 9))

Abstract

Geographical distribution is widely held to be a major determinant of evolutionary dynamics. Correspondingly, genetic programming theorists and practitioners have long developed, used, and studied systems in which populations are structured in quasi-geographical ways. Here we show that a remarkably simple version of this idea produces surprisingly dramatic improvements in problem-solving performance on a suite of test problems. The scheme is trivial to implement, in some cases involving little more than the addition of a modulus operation in the population access function, and yet it provides significant benefits on all of our test problems (ten symbolic regression problems and a quantum computing problem). We recommend the broader adoption of this form of “trivial geography” in genetic programming systems.

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References

  • Andre, David and Koza, John R. (1996). A parallel implementation of genetic programming that achieves super-linear performance. In Arabnia, Hamid R., editor, Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, volume III, pages 1163–1174, Sunnyvale. CSREA.

    Google Scholar 

  • Avise, J. C. (2000). Phylogeography: The History and Formation of Species. Harvard University Press.

    Google Scholar 

  • Axelrod, R., Hammond, R. A., and Grafen, A. (2004). Altruism via kin-selection strategies that rely on arbitrary tags with which they coevolve. Evolution, 58(8):1833–1838.

    Google Scholar 

  • Banzhaf, Wolfgang, Nordin, Peter, Keller, Robert E., and Francone, Frank D. (1998). Genetic Programming — An Introduction; On the Automatic Evolution of Computer Programs and its Applications. Morgan Kaufmann.

    Google Scholar 

  • Barnum, Howard, Bernstein, Herbert J, and Spector, Lee (2000). Quantum circuits for OR and AND of ORs. Journal of Physics A: Mathematical and General, 33(45):8047–8057.

    Article  MathSciNet  Google Scholar 

  • Bryden, Kenneth M., Ashlock, Daniel A., Corns, Steven, and Willson, Stephen J. (2005). Graph based evolutionary algorithms. IEEE Transactions on Evolutionary Computation, forthcoming.

    Google Scholar 

  • Burke, Edmund K., Gustafson, Steven, and Kendall, Graham (2004). Diversity in genetic programming: An analysis of measures and correlation with fitness. IEEE Transactions on Evolutionary Computation, 8(1):47–62.

    Article  Google Scholar 

  • Collins, Robert J. and Jefferson, David R. (1991). Selection in massively parallel genetic algorithms. In Belew, Rick and Booker, Lashon, editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 249–256, San Mateo, CA. Morgan Kaufman.

    Google Scholar 

  • Crawford-Marks, Raphael and Spector, Lee (2002). Size control via size fair genetic operators in the PushGP genetic programming system. In Langdon, W. B., Cantú-Paz, E., Mathias, K., Roy, R., Davis, D., Poli, R., Balakrishnan, K., Honavar, V., Rudolph, G., Wegener, J., Bull, L., Potter, M. A., Schultz, A. C, Miller, J. F., Burke, E., and Jonoska, N., editors, GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, pages 733–739, New York. Morgan Kaufmann Publishers.

    Google Scholar 

  • D’haeseleer, Patrik and Bluming, Jason (1994). Effects of locality in individual and population evolution. In Kinnear, Jr., Kenneth E., editor, Advances in Genetic Programming, chapter 8, pages 177–198. MIT Press.

    Google Scholar 

  • Droste, Stefan, Jansen, Thomas, and Wegener, Ingo (1999). Perhaps not a free lunch but at least a free appetizer. In Banzhaf, Wolfgang, Daida, Jason, Eiben, Agoston E., Garzon, Max H., Honavar, Vasant, Jakiela, Mark, and Smith, Robert E., editors, Proceedings of the Genetic and Evolutionary Computation Conference, volume 1, pages 833–839, Orlando, Florida, USA. Morgan Kaufmann.

    Google Scholar 

  • Eshel, I. (1972). On the neighbor effect and the evolution of altruistic traits. Theoretical Population Biology, 3:258–277.

    Article  MATH  MathSciNet  Google Scholar 

  • Fernandez, Francisco, Tomassini, Marco, and Vanneschi, Leonardo (2003). An empirical study of multipopulation genetic programming. Genetic Programming and Evolvable Machines, 4(1):21–51.

    Article  Google Scholar 

  • Folino, G., Pizzuti, C, Spezzano, G., Vanneschi, L., and Tomassini, M. (2003). Diversity analysis in cellular and multipopulation genetic programming. In Sarker, Ruhul, Reynolds, Robert, Abbass, Hussein, Tan, Kay Chen, McKay, Bob, Essam, Daryl, and Gedeon, Tom, editors, Proceedings of the 2003 Congress on Evolutionary Computation CEC2003, pages 305–311, Canberra. IEEE Press.

    Google Scholar 

  • Folino, Gianluigi, Pizzuti, Clara, and Spezzano, Giandomenico (1999). A cellular genetic programming approach to classification. In Banzhaf, Wolfgang, Daida, Jason, Eiben, Agoston E., Garzon, Max H., Honavar, Vasant, Jakiela, Mark, and Smith, Robert E., editors, Proceedings of the Genetic and Evolutionary Computation Conference, volume 2, pages 1015–1020, Orlando, Florida, USA. Morgan Kaufmann.

    Google Scholar 

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

    Google Scholar 

  • Holland, J. H. (1995). Hidden Order: How Adaptation Builds Complexity. Perseus Books.

    Google Scholar 

  • Klein, Jon (2002). BREVE: a 3d environment for the simulation of decentralized systems and artificial life. In Standish, R. K., Bedau, M. A., and Abbass, H. A., editors, Proceedings of Artificial Life VIII, the 8th International Conference on the Simulation and Synthesis of Living Systems, pages 329–334. The MIT Press. http://www.spiderland.org/breve/breve-klein-alife2002.pdf.

    Google Scholar 

  • Koza, John R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge, MA, USA.

    Google Scholar 

  • Koza, John R. (1994). Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge Massachusetts.

    Google Scholar 

  • Lieberman, E., Hauert, C, and Nowak, M. A. (2005). Evolutionary dynamics on graphs. Nature, 433:312–316.

    Article  Google Scholar 

  • Maruyama, Tsutomu, Hirose, Tetsuya, and Konagaya, Akihiko (1993). A fine-grained parallel genetic algorithm for distributed parallel systems. In Forrest, Stephanie, editor, Proc. of the Fifth Int. Conf. on Genetic Algorithms, pages 184–190, San Mateo, CA. Morgan Kaufmann.

    Google Scholar 

  • Mayr, Ernst (1942). Systematics and the origin of species from the viewpoint of a zoologist. Columbia University Press.

    Google Scholar 

  • Nowak, M. A. and May, R. M. (1992). Evolutionary games and spatial chaos. Nature, 359:826–829.

    Article  Google Scholar 

  • Nowostawski, M. and Poll, R. (1999). Parallel genetic algorithm taxonomy.

    Google Scholar 

  • Ofria, Charles and Wilke, Claus O. (2004). Avida: A software platform for research in computational evolutionary biology. Artificial Life, 10(2): 191–229.

    Article  Google Scholar 

  • Pettey, Chrisila C. (1997). Diffusion (cellular) models. In Bäck, Thomas, Fogel, David B., and Michalewicz, Zbigniew, editors, Handbook of Evolutionary Computation, pages C6.4:1–6. Institute of Physics Publishing and Oxford University Press, Bristol, New York.

    Google Scholar 

  • Ray, Thomas S. (1991). Is it alive or is it GA. In Belew, Richard K. and Booker, Lashon B., editors, Proceedings of the Fourth International Conference on Genetic Algorithms, pages 527–534, University of California-San Diego, La Jolla, CA, USA. Morgan Kaufmann.

    Google Scholar 

  • Spector, Lee (2001). Autoconstructive evolution: Push, pushGP, and pushpop. In Spector, Lee, Goodman, Erik D., Wu, Annie, Langdon, W. B., Voigt, Hans-Michael, Gen, Mitsuo, Sen, Sandip, Dorigo, Marco, Pezeshk, Shahram, Garzon, Max H., and Burke, Edmund, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pages 137–146, San Francisco, California, USA. Morgan Kaufmann.

    Google Scholar 

  • Spector, Lee (2004). Automatic Quantum Computer Programming: A Genetic Programming Approach, volume 7 of Genetic Programming. Kluwer Academic Publishers, Boston/Dordrecht/New York/London. in press.

    Google Scholar 

  • Spector, Lee, Barnum, Howard, Bernstein, Herbert J., and Swamy, Nikhil (1999). Finding a better-than-classical quantum AND/OR algorithm using genetic programming. In Angeline, Peter J., Michalewicz, Zbyszek, Schoenauer, Marc, Yao, Xin, and Zalzala, Ali, editors, Proceedings of the Congress on Evolutionary Computation, volume 3, pages 2239–2246, Mayflower Hotel, Washington D.C., USA. IEEE Press.

    Google Scholar 

  • Spector, Lee and Klein, Jon (2005a). Genetic stability and territorial structure facilitate the evolution of tag-mediated altruism. Artificial Life. Forthcoming.

    Google Scholar 

  • Spector, Lee and Klein, Jon (2005b). Machine invention of quantum computing circuits by means of genetic programming. In preparation.

    Google Scholar 

  • Spector, Lee, Klein, Jon, and Keijzer, Maarten (2005). The push3 execution stack and the evolution of control. In Proc. of the Genetic and Evolutionary Computation Conference. Springer-Verlag.

    Google Scholar 

  • Spector, Lee and Robinson, Alan (2002). Genetic programming and autoconstructive evolution with the push programming language. Genetic Programming and Evolvable Machines, 3(1):7–40.

    Article  Google Scholar 

  • Wolpert, David H. and Macready, William G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1):67–82.

    Article  Google Scholar 

  • Wright, Sewall (1945). Tempo and mode in evolution: a critical review. Ecology, 26:415–419.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Cognitive Science, Hampshire College, Amherst, MA, 01002-3359, USA

    Lee Spector & Jon Klein

  2. Physical Resource Theory, Chalmers University of Technology & Göteborg University, Göteborg, Sweden

    Jon Klein

Authors
  1. Lee Spector
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  2. Jon Klein
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Editor information

Editors and Affiliations

  1. Chevron Information Technology Company, USA

    Tina Yu

  2. Center for the Study of Complex Systems, University of Michigan, USA

    Rick Riolo

  3. Genetics Squared, Inc., USA

    Bill Worzel

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© 2006 Springer Science+Business Media, Inc.

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Spector, L., Klein, J. (2006). Trivial Geography in Genetic Programming. In: Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice III. Genetic Programming, vol 9. Springer, Boston, MA. https://doi.org/10.1007/0-387-28111-8_8

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  • DOI: https://doi.org/10.1007/0-387-28111-8_8

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-28110-0

  • Online ISBN: 978-0-387-28111-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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