Sciweavers

GECCO
2004
Springer

CellNet Co-Ev: Evolving Better Pattern Recognizers Using Competitive Co-evolution

14 years 4 months ago
CellNet Co-Ev: Evolving Better Pattern Recognizers Using Competitive Co-evolution
A model for the co-evolution of patterns and classifiers is presented. The CellNet system for generating binary classifiers is used as a base for experimentation. The CellNet system is extended to include a competitive coevolutionary Genetic Algorithm, where patterns evolve as well as classifiers; This is facilitated by the addition of a set of topologically-invariant camouflage functions, through which images may disguise themselves. This allows for the creation of a larger and more varied image database, and also artificially increases the difficulty of the classification problem. Application to the CEDAR database of hand-written characters yields both an increase in reliability and an elimination of over-fitting relative to the original CellNet project.
Taras Kowaliw, Nawwaf N. Kharma, Chris Jensen, Hus
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where GECCO
Authors Taras Kowaliw, Nawwaf N. Kharma, Chris Jensen, Hussein Moghnieh, Jie Yao
Comments (0)