By Topic

Inductive bias and genetic programming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
P. A. Whigham ; New South Wales Univ., Kensington, NSW, Australia

Many engineering problems may be described as a search for one near optimal description amongst many possibilities, given certain constraints. Search techniques such as genetic programming, seem appropriate to represent many problems. The paper describes a grammatically based learning technique based upon the genetic programming paradigm, that allows declarative biasing and modifies the bias as the evolution proceeds. The use of bias allows complex problems to be represented and searched efficiently

Published in:

Genetic Algorithms in Engineering Systems: Innovations and Applications, 1995. GALESIA. First International Conference on (Conf. Publ. No. 414)

Date of Conference:

12-14 Sep 1995