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

Created by W.Langdon from gp-bibliography.bib Revision:1.8620

@TechReport{koza:1994:aao,

• author = "John R. Koza",
• title = "Architecture-Altering Operations for Evolving the Architecture of a Multipart Program in Genetic Programming",
• 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 = "http://www.genetic-programming.com/jkpdf/tr1528.pdf",
• broken = "ftp://reports.stanford.edu/pub/cstr/reports/cs/tr/94/1528/CS-TR-94-1528.ps",
• URL = "http://www-db.stanford.edu/TR/CS-TR-94-1528.html",
• 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 operations.",
• notes = "See also \cite{koza:1995:ea}

  http://i.stanford.edu/pub/cstr/reports/cs/tr/94/1528/ also contains GIF and MAC versions",

• size = "57 pages",

}

Genetic Programming entries for John Koza

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