- author = "Naoki Mori and R. I. (Bob) McKay and Xuan Hoai Nguyen and Daryl Essam",
- title = "How Different are Genetic Programs? Entropy Methods for Studying Diversity and Complexity in Genetic Programming",
- booktitle = "11th Asia-Pacific Workshop on Intelligent and Evolutionary Systems: IES 2007",
- year = "2007",
- pages = "8 pages",
- address = "Yokosuka, Kanagawa, Japan",
- month = "30 " # nov # "--2 " # dec,
- keywords = "genetic algorithms, genetic programming, theory, Equivalent Decision Simplification",
-
URL = "
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.107.9011&rep=rep1&type=pdf",
-
URL = "https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-18700227/",
-
URL = "https://cir.nii.ac.jp/crid/1574231875440322560",
- size = "8 pages",
-
abstract = "We propose a new approach to the study of Genetic
Programming dynamics, using genotypic entropy metrics.
The aim of the approach is to provide a single
framework for simultaneously studying diversity and
individual complexity, both of the raw trees and their
non-redundant sub-components. The entropy metrics are
based on the entropy of small subtrees, and we show
that the analysis is largely independent of the exact
choice of subtree shape.
To facilitate the study of redundancy, we apply powerful new methods for detecting and removing redundancy; while these methods are tailored to the particular function set used here, they are readily extensible to other function sets.
We demonstrate the effectiveness of the approach by applying it to a well-known symbolic regression problem. Using the new methods, we measure quantitative relationships between solution complexity and diversity, explore relationships between population structure and problem success or failure, and analyse the relationships between the different solutions found by GP.",
- notes = "cos(2x), analysis small fixed templates",
