Evolving Teams of Predictors with Linear Genetic Programming

1. W. Banzhaf P. Nordin R. Keller, and F. Francone, Genetic Programming-An Introduction. On the Automatic Evolution of Computer Programs and its Application, dpunkt/Morgan Kaufman: Heidelberg/San Francisco, 1998.

   Google Scholar 

2. M. Brameier and W. Banzhaf, “A comparison of linear genetic programming and neural networks in medical data mining,” IEEE Trans. Evolutionary Comput., vol. 5(1), pp. 17-26, 2001.

   Google Scholar 

3. L. K. Hansen and P. Salamon, “Neural network ensembles,” IEEE Trans. Pattern Analysis and Mach, Intell., vol. 12(10), pp. 993-1001, 1990.

   Google Scholar 

4. T. Haynes S. Sen D. Schoenefeld, and R. Wainwright, “Evolving a team,” in Working Notes for the AAAI Symposium on Genetic Programming, MIT Press: Cambridge, MA, 1995.

   Google Scholar 

5. T. Haynes and S. Sen, “Crossover operators for evolving a team,” in Genetic Programming 1997: Proc. Second Ann. Conf., John R. Koza Kalyanmoy Deb Marco Dorigo David B. Fogel Max Garzon Hitoshi Iba, and Rick L. Riolo (eds.), Morgan Kaufmann: San Francisco, CA, 1997, pp. 162-167.

   Google Scholar 

6. J. Koza, Genetic Programming, MIT Press: Cambridge, MA, 1992.

   Google Scholar 

7. A. Krogh and J. Vedelsby, “Neural network ensembles, cross validation, and active learning,” in Advances in Neural Information Processing Systems, G. Tesauro D. S. Touretzky and T. K. Leen (eds.), vol. 7, MIT Press: Cambridge, MA, 1995, pp. 231-238.

   Google Scholar 

8. S. Luke and L. Spector, “Evolving teamwork and coordination with genetic programming,” in Genetic Programming 1996: Proc. First Ann. Conf., J. R. Koza D. E. Goldberg David B. Fogel, and Rick L. Riolo (eds.), MIT Press: Cambridge, MA, 1996, pp. 150-156.

   Google Scholar 

9. P. Nordin, “A compiling genetic programming system that directly manipulates the machine-code,” in Advances in Genetic Programming, K. E. Kinnear (ed.), MIT Press, Cambridge, MA, 1994, pp. 311-331.

   Google Scholar 

10. M. P. Perrone and L. N. Cooper, “When networks disagree: Ensemble methods for neural networks,” in Neural Network for Speech and Image Processing, R. J. Mammone (ed.), Chapman-Hall: London, 1993, pp. 126-142.

    Google Scholar 

11. M. Riedmiller and H. Braun, “A direct adaptive method for faster backpropagation learning: The RPROP algorithm,” in Proc. IEEE Int. Conf. Neural Networks, San Francisco, CA, 1993, pp. 586-591.

12. H.-P. Schwefel, Evolution and Optimum Seeking, Wiley: New York, 1995.

    Google Scholar 

13. R. L. Somorjai A. E. Nikulin N. Pizzi D. Jackson G. Scarth B. Dolenko H. Gordon P. Russell C. L. Lean L. Delbridge C. E. Mountford, and I. C. P. Smith, “Computetized consensus diagnosis-A classification strategy for the robust analysis of MR spectra. 1. Application to H-l Spectra of Thyroid Neoplasma,” Magnetic Resonance in Medicine, vol. 33, pp. 257-263, 1995.

    Google Scholar 

14. T. Soule, “Voting Teams: A cooperative approach to non-typical problems using genetic programming,” in Proc. Int. Conf. Genetic and Evolutionary Comput., W. Banzhaf J. Daida A. E. Eiben M. H. Garzon V. Honavar M. Jakiela, and R. E. Smith (eds.), Morgan Kaufmann: San Francisco, CA, 1999, pp. 916-922.

    Google Scholar 

15. T. Soule, “Heterogeneity and Specialization in Evolving Teams,” in Proc. Second Int. Conf. Genetic and Evolutionary Comput., Darrell Whitley David Goldberg Erick Cantu-Paz Lee Spector Ian Parmee, and Hans-Georg Beyer (eds.), Morgan Kaufmann: San Francisco, CA, 2000, pp. 778-785.

    Google Scholar 

16. W. A. Tackett, Recombination, Selection and the Genetic Construction of computer programs. Ph.D. thesis, University of Southern California, Department of Electrical Engineering Systems, 1994.

17. D. H. Wolpert, “Stacked generalization,” Neural Networks, vol. 5(2), pp. 241-260, 1992.

    Google Scholar 

18. X. Yao and Y. Liu, “Making use of population information in evolutionary artificial neural networks,” IEEE Trans. Systems, Man and Cybernetics, vol. 28B(3), pp. 417-425, 1998.

    Google Scholar 

19. B.-T. Zhang and J.-G. Joung, “Enhancing robustness of genetic programming at the dpecies level,” in Genetic Programming 1996: Proc. First Ann. Conf., J. R. Koza D. E. Goldberg David B. Fogel, and Rick L. Riolo (eds.), MIT Press: Cambridge, MA, 1996, pp. 336-342.

    Google Scholar 

Download references