Genetic Programming with Adaptive Representations

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Justinian P. Rosca and Dana H. Ballard",
  title =        "Genetic Programming with Adaptive Representations",
  institution =  "University of Rochester, Computer Science Department",
  address =      "Rochester, NY, USA",
  number =       "TR 489",
  month =        feb,
  year =         "1994",
  keywords =     "genetic algorithms, genetic programming, learning,
                 adaptive representation",
  URL =          "",
  abstract =     "Machine learning aims towards the acquisition of
                 knowledge based on either experience from the
                 interaction with the external environment or by
                 analyzing the internal problem-solving traces. Both
                 approaches can be implemented in the Genetic
                 Programming (GP) paradigm. \cite{Hillis90} proves in an
                 ingenious way how the first approach can work. There
                 have not been any significant tests to prove that GP
                 can take advantage of its own search traces. This paper
                 presents an approach to automatic discovery of
                 functions in GP based on the ideas of discovery of
                 useful building blocks by analyzing the evolution
                 trace, generalizing of blocks to define new functions
                 and finally adapting of the problem representation
                 on-the-fly. Adaptation of the representation determines
                 a hierarchical organization of the extended function
                 set which enables a restructuring of the search space
                 so that solutions can be found more easily. Complexity
                 measures of solution trees are defined for an adaptive
                 representation framework and empirical results are
  notes =        "Jan 1995, Our printer barfed on
                 file at page 23 figure 13.

                 Thu, 16 Feb 95 TR489 can be found in the same ftp
                 directory (pub/u/rosca/gp) under the name

                 A shorter version can be found in

Genetic Programming entries for Justinian Rosca Dana H Ballard