Page last updated on
15 Nov 95. Created page
This is the abstract for the paper that I presented at the AAAI Fall
Symposium on Genetic Programming in November, 1995.
Dynamic Classifiers: Genetic Programming and Classifier Systems
Patrick Tufts
Department of Computer Science
Volen Center for Complex Systems
Brandeis University
Waltham, Mass.
email: zippy@cs.brandeis.edu
Abstract
The Dynamic Classifier System extends the traditional classifier
system by replacing its fixed-width ternary representation with Lisp
expressions. Genetic programming applied to the classifiers allows
the system to discover building blocks in a flexible, fitness
directed manner.
In this paper, I describe the prior art of problem decomposition
using genetic programming and classifier systems. I then show how
the proposed system builds on work in these two areas, extending
them in a way that provides for flexible representation and fitness
directed discovery of useful building blocks.