Prototype code for integrating ExSTraCS rule evolution with GP tree evolution in a 'co-evolution' inspired framework.
The aim of this project is to get a machine learning algorithm (in this case the ExSTraCS Learning Classifier System algorithm) to automatically determine the best represenation to use in modelinging the data without prior knowledge of the given problem.
We also expect this adapatation to perform better in regression problems than our previous Continuous endpoint ExSTraCS algorithm.