- author = "Richard Preen and Larry Bull",
- title = "Discrete dynamical genetic programming in XCS",
- booktitle = "GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation",
- year = "2009",
- editor = "Guenther Raidl and Franz Rothlauf and Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and Mauro Birattari and Clare Bates Congdon and Martin Middendorf and Christian Blum and Carlos Cotta and Peter Bosman and Joern Grahl and Joshua Knowles and David Corne and Hans-Georg Beyer and Ken Stanley and Julian F. Miller and Jano {van Hemert} and Tom Lenaerts and Marc Ebner and Jaume Bacardit and Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and Thomas Jansen and Riccardo Poli and Enrique Alba",
- pages = "1299--1306",
- address = "Montreal",
- publisher = "ACM",
- publisher_address = "New York, NY, USA",
- month = "8-12 " # jul,
- organisation = "SigEvo",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-1-60558-325-9",
- bibsource = "DBLP, http://dblp.uni-trier.de",
-
DOI = "
doi:10.1145/1569901.1570075",
- abstract = "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.",
-
notes = "GECCO-2009 A joint meeting of the eighteenth
international conference on genetic algorithms
(ICGA-2009) and the fourteenth annual genetic
programming conference (GP-2009).
ACM Order Number 910092.",
