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.


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.

Patrick Tufts