Continuously Evolving Programs in Genetic Programming Using Gradient Descent
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @TechReport{vuw-CS-TR-04-10,
-
author = "Will Smart and Mengjie Zhang",
-
title = "Continuously Evolving Programs in Genetic Programming
Using Gradient Descent",
-
institution = "Computer Science, Victoria University of Wellington",
-
year = "2004",
-
number = "CS-TR-04-10",
-
address = "New Zealand",
-
keywords = "genetic algorithms, genetic programming",
-
URL = "http://www.mcs.vuw.ac.nz/comp/Publications/CS-TR-04-10.abs.html",
-
URL = "http://www.mcs.vuw.ac.nz/comp/Publications/archive/CS-TR-04/CS-TR-04-10.pdf",
-
abstract = "gradient descent search in genetic programming for
continuously evolving genetic programs for object
classification problems. An inclusion factor is
introduced to each node except the root node in a
genetic program and gradient descent search is applied
to the inclusion factors. Three new on-zero operators
and two new continuous genetic operators are developed
for evolution. This approach is examined and compared
with a basic GP approach on three object classification
problems of varying difficulty. The results suggest
that the new approach can evolve genetic programs
continuously. The new method which uses the standard
genetic operators and gradient descent search applied
to the inclusion factors substantially outperforms the
basic GP approach which uses the standard genetic
operators but does not use the gradient descent and
inclusion factors. However, the new method with the
continuous operators and the gradient descent on
inclusion factors decreases the performance on all the
problems.",
- }
Genetic Programming entries for
Will Smart
Mengjie Zhang
Citations