Automated Synthesis by Means of Genetic Programming of Complex Structures Incorporating Reuse, Parameterized Reuse, Hierarchies, and Development

  • John R. Koza
  • Matthew J. Streeter
  • Martin A. Keane
Part of the Genetic Programming Series book series (GPEM, volume 6)


Genetic programming can be used as an automated invention machine to synthesize designs for complex structures. In particular, genetic programming has automatically synthesized complex structures that infringe, improve upon, or duplicate the functionality of 21 previously patented inventions (including analog electrical circuits, controllers, and mathematical algorithms). Genetic programming has also generated two patentable new inventions (involving controllers). Genetic programming has also generated numerous additional human-competitive results involving the design of quantum computing circuits as well as other substantial results involving antennae, networks of chemical reactions (metabolic pathways), and genetic networks. We believe that these results are the direct consequence of a group of techniques-many unique to genetic programming-that facilitate the automatic synthesis of complex structures. These techniques include automatic reuse, parameterized reuse, parameterized topologies, and developmental genetic programming. The paper describes these techniques and how they contribute to automated design.

Key words

Hierarchy reuse development parameterized topologies architecture-altering operations automatically defined functions automatically defined iterations automatically defined loops automatically defined recursions automatically defined stores circuits controllers 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Astrom, Karl J. and Hagglund, Tore. (1995). PID Controllers: Theory, Design, and Tuning. Second Edition. Research Triangle Park, NC: Instrument Society of America.Google Scholar
  2. Banzhaf, Wolfgang, Nordin, Peter, Keller, Robert E., and Francone, Frank D. (1998). Genetic Programming - An Introduction. San Francisco, CA: Morgan Kaufmann and Heidelberg: dpunkt.zbMATHGoogle Scholar
  3. Barnum, H., Bernstein, H. J. and Spector, Lee (2000). Quantum circuits for OR and AND of ORs. Journal of Physics A: Mathematical and General 33(45): 8047–8057.MathSciNetzbMATHCrossRefGoogle Scholar
  4. Fraser, C. M, Gocayne, J. D., White, O., Adams, M. D., Clayton, R. A., Fleischmann, R. D., Bult, C. J., Kerlavage, A. R., Sutton, G, Kelley, J. M., et al. (1995). The Minimal Gene Complement of Mycoplasma genitalium. Science 270(5235): 397–403.CrossRefGoogle Scholar
  5. Goldberg, David E. (2002). The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Boston: Kluwer Academic Publishers.zbMATHGoogle Scholar
  6. Holland, John H. (1992). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Ann Arbor, MI: University of Michigan Press, 1975. Second edition. Cambridge, MA: The MIT Press.Google Scholar
  7. Keane, Martin A., Koza, John R., and Streeter, Matthew J. (2002). Improved General- Purpose Controllers. U. S. patent application filed July 12, 2002.Google Scholar
  8. Koza, John R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA: MIT Press.zbMATHGoogle Scholar
  9. Koza, John R. (1994). Genetic Programming II: Automatic Discovery of Reusable Programs. Cambridge, MA: MIT Press.zbMATHGoogle Scholar
  10. Koza, John R., Bennett III, Forrest, H., Andre, David, and Keane, Martin A. (1999). Genetic Programming III: Darwinian Invention and Problem Solving. San Francisco, CA: Morgan Kaufmann.zbMATHGoogle Scholar
  11. Koza, John R., Keane, Martin A., Streeter, Matthew J., Mydlowec, William, Yu, Jessen, and Lanza, Guido. (2003). Genetic Programming IV. Routine Human-Competitive Machine Intelligence. Kluwer Academic Publishers.Google Scholar
  12. Langdon, William B. (1998). Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! Amsterdam: Kluwer.Google Scholar
  13. Langdon, William B. and Poli, Riccardo. (2002). Foundations of Genetic Programming. Springer-Verlag.zbMATHGoogle Scholar
  14. Ohno, Susumu. (1970). Evolution by Gene Duplication. New York: Springer-Verlag.Google Scholar
  15. Spector, Lee, Barnum, Howard, and Bernstein, Herbert, J. (1998) Genetic programming for quantum computers. In Koza, John R., Banzhaf, Wolfgang, Chellapilla, Kumar, Deb, Kalyanmoy, Dorigo, Marco, Fogel, David B., Garzon, Max H., Goldberg, David E., Iba, Hitoshi, and Riolo, Rick, (editors). Genetic Programming 1998: In Proceedings of the Third Annual Conference, 365–373. San Francisco, CA: Morgan Kaufmann.Google Scholar
  16. Spector, Lee, Barnum, Howard, and Bernstein, Herbert J. (1999). Quantum computing applications of genetic programming. In Spector, Lee, Langdon, William B., O'Reilly, Una-May, and Angeline, Peter (editors). Advances in Genetic Programming 3. Cambridge, MA: The MIT Press, 1999. 135–160.Google Scholar
  17. Spector, Lee, Barnum, Howard, Bernstein, Herbert J., and Swamy, N. (1999). Finding a Better-than-classical Quantum AND/OR Algorithm Using Genetic Programming. In IEEE. In Proceedings of 1999 Congress on Evolutionary Computation, pp. 2239–2246. Piscataway, NJ, IEEE Press.Google Scholar
  18. Spector, Lee, and Bernstein, Herbert J. (2003). Communication Capacities of Some Quantum Gates, Discovered in part through Genetic Programming. In Shapiro, Jeffery H. and Hirota, Osamu (editors). In Proceedings of the Sixth International Conference on Quantum Communication, Measurement, and Computing, 500–503. Princeton, NJ: Rinton Press.Google Scholar
  19. Ziegler, J. G. and Nichols, N. B. (1942). Optimum Settings for Automatic Controllers. Transactions of ASME 64: 759–768Google Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • John R. Koza
    • 1
  • Matthew J. Streeter
    • 2
  • Martin A. Keane
    • 3
  1. 1.Stanford UniversityStanfordUSA
  2. 2.Genetic Programming Inc.Mountain ViewUSA
  3. 3.Econometrics Inc.ChicagoUSA

Personalised recommendations