Online Feature-Generation of Code Fragments for XCS to Guide Feature Construction
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Nguyen:2019:CEC,
-
author = "Trung B. Nguyen and Will N. Browne and Mengjie Zhang",
-
title = "Online Feature-Generation of Code Fragments for {XCS}
to Guide Feature Construction",
-
booktitle = "2019 IEEE Congress on Evolutionary Computation (CEC)",
-
year = "2019",
-
pages = "3308--3315",
-
month = jun,
-
keywords = "genetic algorithms, genetic programming",
-
DOI = "doi:10.1109/CEC.2019.8789950",
-
abstract = "Code Fragments (CFs) are a new representation for
classifier conditions in Learning Classifier Systems
(LCSs). CFs are Genetic Programming-like trees that use
functions as internal nodes, and data input or
previously learned CFs as leaf nodes for feature
construction. The XCSCFC system used CFs in rule
conditions of XCS, an accuracy-based Michigan-style
LCS, to transfer knowledge and thus solve large-scale
problems. However, the trade-off for the richness and
flexibility that allows CFs to compactly describe
decision boundaries results in an undesired increase in
the search space of solutions. Therefore, this paper
proposes a novel model extension for Online
Feature-generation (OF), which enables evolving
features (CFs) through an online observed list of CFs.
This extension enables a method of estimating the worth
of CFs to identifying the patterns in the problem in
order to construct applicable high-level features. The
experiments show that the XCS with OF (XOF) can solve
the benchmark problems in fewer generations compared
with XCSCFC in non-transfer learning scenarios. The
novel search of CFs successfully built high-level
features, which show the rules produced by XOF to be
more generalised than previously possible.
Consequently, the final solutions contain fewer rules
to solve problems as they encode more compact and
comprehensive decision boundaries.",
-
notes = "Also known as \cite{8789950}",
- }
Genetic Programming entries for
Trung Bao Nguyen
Will N Browne
Mengjie Zhang
Citations