Architecture-Altering Operations for Evolving the Architecture of a Multipart Program in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "John R. Koza",
  title =        "Architecture-Altering Operations for Evolving the
                 Architecture of a Multipart Program in Genetic
  type =         "Technical Report",
  number =       "{STAN}-{CS}-94-1528",
  institution =  "Dept. of Computer Science, Stanford University",
  keywords =     "genetic algorithms, genetic programming",
  year =         "1994",
  address =      "Stanford, California 94305, USA",
  month =        oct,
  URL =          "",
  broken =       "",
  URL =          "",
  abstract =     "Previous work described a way to evolutionarily select
                 the architecture of a multi-part computer program From
                 among preexisting alternatives in the population while
                 concurrently solving a problem during a run of genetic
                 programming. This report describes six new
                 architecture-altering operations that provide a way to
                 evolve the architecture of a multi-part program in the
                 sense of actually changing the architecture of programs
                 dynamically during the run. The new
                 architecture-altering operations are motivated by the
                 naturally occurring operation of gene duplication as
                 described in Susumu Ohno's provocative 1970 book
                 Evolution by Means of Gene Duplication as well as the
                 naturally occurring operation of gene deletion. The six
                 new architecture-altering operations are branch
                 duplication, argument duplication, branch creation,
                 argument creation, branch deletion and argument
                 deletion. A connection is made between genetic
                 programming and other techniques of automated problem
                 solving by interpreting the architecture-altering
                 operations as providing an automated way to specialize
                 and generalize programs. The report demonstrates that a
                 hierarchical architecture can be evolved to solve an
                 illustrative symbolic regression problem using the
                 architecture- altering operations. Future work will
                 study the amount of additional computational effort
                 required to employ the architecture-altering
  notes =        "See also

                 also contains GIF and MAC versions",
  size =         "57 pages",

Genetic Programming entries for John Koza