# Evolution of Both the Architecture and the Sequence of Work-Performing Steps of a Computer Program Using Genetic Programming with Architecture-Altering Operations

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

@InProceedings{koza:1995:earch,
author =       "John R. Koza and David Andre",
title =        "Evolution of Both the Architecture and the Sequence of
Work-Performing Steps of a Computer Program Using
Genetic Programming with Architecture-Altering
Operations",
booktitle =    "Working Notes for the AAAI Symposium on Genetic
Programming",
year =         "1995",
editor =       "E. V. Siegel and J. R. Koza",
pages =        "50--60",
address =      "MIT, Cambridge, MA, USA",
publisher_address = "445 Burgess Drive, Menlo Park, CA 94025, USA",
month =        "10--12 " # nov,
publisher =    "AAAI",
keywords =     "genetic algorithms, genetic programming",
URL =          "http://www.genetic-programming.com/jkpdf/aaai1995fallsymaatm.pdf",
URL =          "http://www.aaai.org/Papers/Symposia/Fall/1995/FS-95-01/FS95-01-007.pdf",
URL =          "http://www.aaai.org/Library/Symposia/Fall/fs95-01.php",
size =         "11 pages",
abstract =     "The goal of automatic programming is to create, in an
automated way, a computer program that enables a
computer to solve a problem. Ideally, an automatic
programming system should require that the user
pre-specify as little as possible about the problem
environment. In particular, it is desirable that the
user not be required to prespecify the architecture of
the ultimate solution to his problem.

The question of how to automatically create the
architecture of the overall program in an evolutionary
approach to automatic programming, such as genetic
programming, has a parallel in the biological world:
how new structures and behaviors are created in living
things. This corresponds to the question of how new DNA
that encodes for a new protein is created in more
complex organisms.

This chapter describes how the biological theory of
gene duplication described in Susumu Ohno's provocative
book, Evolution by Means of Gene Duplication, was
brought to bear on the problem of architecture
discovery in genetic programming. The resulting
biologically-motivated approach uses six new
architecture-altering operations to enable genetic
programming to automatically discover the architecture
of the solution at the same time as genetic programming
is evolving a solution to the problem.

Genetic programming with the architecture-altering
operations is used to evolve a computer program to
classify a given protein segment as being a
transmembrane domain or non-transmembrane area of the
protein (without biochemical knowledge, such as the
hydrophobicity values used in human-written algorithms
for this task). The best genetically-evolved program
achieved an out-of-sample error rate that was better
than that reported for other previously reported
human-written algorithms. This is an instance of an
automated machine learning algorithm matching human
performance on a non-trivial problem.",
notes =        "AAAI-95f GP. Part of \cite{siegel:1995:aaai-fgp} {\em
Telephone:} 415-328-3123 {\em Fax:} 415-321-4457 {\em
email} info@aaai.org {\em URL:} http://www.aaai.org/
Transmembrane protien classification 'out of sample
error rate that was better than that previously
reported for other previously repored human-written
algorithms' [p50]",
}



Genetic Programming entries for John Koza David Andre

Citations