Discrete Dynamical Genetic Programming in XCS

Details Discrete Dynamical Genetic Programming in XCS Discrete Dynamical Genetic Programming in XCS

2012-04-18

arxiv.org/abs/1204.4200v1

Preen, R.J. and Bull, L. (2009) Discrete dynamical genetic programming in XCS. In Proceedings of the 11th Annual conference on

Computer Science

Artificial Intelligence

arXiv admin note: substantial text overlap with arXiv:1201.5604

Scientific paper

A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using a discrete dynamical system representation within the XCS Learning Classifier System. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such discrete dynamical systems within XCS to solve a number of well-known test problems.

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