Research Repository

Memory with Memory in Genetic Programming

Poli, Riccardo and McPhee, Nicholas Freitag and Citi, Luca and Crane, Ellery (2009) 'Memory with Memory in Genetic Programming.' Journal of Artificial Evolution and Applications, 2009. 1 - 16. ISSN 1687-6229

[img]
Preview
Text
570606.pdf - Published Version
Available under License Creative Commons Attribution.

Download (984kB) | Preview

Abstract

<jats:p>We introduce Memory with Memory Genetic Programming (MwM-GP), where we use soft assignments and soft return operations. Instead of having the new value completely overwrite the old value of registers or memory, soft assignments combine such values. Similarly, in soft return operations the value of a function node is a blend between the result of a calculation and previously returned results. In extensive empirical tests, MwM-GP almost always does as well as traditional GP, while significantly outperforming it in several cases. MwM-GP also tends to be far more consistent than traditional GP. The data suggest that MwM-GP works by successively refining an approximate solution to the target problem and that it is much less likely to have truly ineffective code. MwM-GP can continue to improve over time, but it is less likely to get the sort of exact solution that one might find with traditional GP.</jats:p>

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 13 Mar 2014 10:43
Last Modified: 19 Nov 2018 15:15
URI: http://repository.essex.ac.uk/id/eprint/8789

Actions (login required)

View Item View Item