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BIBLIOGRAPHY                                                  193


            J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors. Genetic Program-
              ming 1996: Proceedings of the First Annual Conference, Stanford University, CA,
              USA, 28–31 July 1996. MIT Press.  URL http://www.genetic-programming.org/
              gp96proceedings.html.                                      GPBiB
            J. R. Koza, K. Deb, M. Dorigo, D. B. Fogel, M. Garzon, H. Iba, and R. L. Riolo, editors.
              Genetic Programming 1997: Proceedings of the Second Annual Conference, Stanford
              University, CA, USA, 13-16 July 1997. Morgan Kaufmann. URL http://www.mkp.com/
              books_catalog/1-55860-483-9.asp.                           GPBiB
            J. R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D. B. Fogel, M. H. Garzon,
              D. E. Goldberg, H. Iba, and R. Riolo, editors. Genetic Programming 1998: Proceedings
              of the Third Annual Conference, University of Wisconsin, Madison, WI, USA, 22-25
              July 1998. Morgan Kaufmann. ISBN 1-55860-548-7.            GPBiB
            D. H. Kraft, F. E. Petry, W. P. Buckles, and T. Sadasivan. The use of genetic programming
              to build queries for information retrieval. In Proceedings of the 1994 IEEE World
              Congress on Computational Intelligence, pages 468–473, Orlando, Florida, USA, 27-
              29 June 1994. IEEE Press.                                  GPBiB
            T. Krantz, O. Lindberg, G. Thorburn, and P. Nordin. Programmatic compression of
              natural video. In E. Cant´u-Paz, editor, Late Breaking Papers at the Genetic and Evo-
              lutionary Computation Conference (GECCO-2002), pages 301–307, New York, NY,
              July 2002. AAAI. URL http://thomas.krantz.com/paper.pdf.   GPBiB
            N. Krasnogor. Self generating metaheuristics in bioinformatics: The proteins structure
              comparison case. Genetic Programming and Evolvable Machines, 5(2):181–201, June
              2004. ISSN 1389-2576.

            K. Krawiec. Evolutionary Feature Programming: Cooperative learning for knowledge
              discovery and computer vision. Number 385. Wydawnictwo Politechniki Poznanskiej,
              Poznan University of Technology, Poznan, Poland, 2004. URL http://idss.cs.put.
              poznan.pl/~krawiec/pubs/hab/krawiec_hab.pdf.               GPBiB

            W. B. Langdon. The evolution of size in variable length representations. In 1998 IEEE
              International Conference on Evolutionary Computation, pages 633–638, Anchorage,
              Alaska, USA, 5-9 May 1998. IEEE Press. URL http://www.cs.bham.ac.uk/~wbl/ftp/
              papers/WBL.wcci98_bloat.pdf.                               GPBiB
            W. B. Langdon. Size fair and homologous tree genetic programming crossovers. In
              W. Banzhaf, et al., editors, Proceedings of the Genetic and Evolutionary Computation
              Conference, volume 2, pages 1092–1097, Orlando, Florida, USA, 13-17 July 1999a.
              Morgan Kaufmann. ISBN 1-55860-611-4. URL http://www.cs.ucl.ac.uk/staff/W.
              Langdon/ftp/papers/WBL.gecco99.fairxo.ps.gz.               GPBiB
            W. B. Langdon. Scaling of program tree fitness spaces. Evolutionary Computation, 7(4):
              399–428, Winter 1999b. ISSN 1063-6560. URL http://www.mitpressjournals.org/
              doi/pdf/10.1162/evco.1999.7.4.399.                         GPBiB
            W. B. Langdon. Convergence rates for the distribution of program outputs. In W. B.
              Langdon, et al., editors, GECCO 2002: Proceedings of the Genetic and Evolution-
              ary Computation Conference, pages 812–819, New York, 9-13 July 2002a. Morgan
              Kaufmann Publishers. ISBN 1-55860-878-8. URL http://www.cs.ucl.ac.uk/staff/
              W.Langdon/ftp/papers/wbl_gecco2002.pdf.                    GPBiB
                                    100             1000            2
                                              Avg Size       Avg Fitness      sin(x)
                                                             Best Fitness    GP (gen=15)
                                    90
                                                                    1.5
                                    80
                                                                    1
                                    70
                                                    100
                                                                    0.5
                                    60
                      Generation 15  Average Size   50  Fitness     0
                                    40                             -0.5
                                                     10
                                    30
                      (see Sec. B.4)   20                          -1
                                                                   -1.5
                                    10
                                                     1             -2
                                     0   20   40   60   80   100   0   20   40   60   80   100   0   1   2   3   4   5   6
                                         Generations     Generations      x
   202   203   204   205   206   207   208   209   210   211   212