On the use of rule-sharing in learning classifier system ensembles

This paper presents an investigation into exploiting the population-based nature of Learning Classifier Systems for their use within highly-parallel systems. In particular, the use of simple accuracybased Learning Classifier Systems within the ensemble machine approach is examined. Results indicate that inclusion of a rule migration mechanism inspired by Parallel Genetic Algorithms is an effective way to improve learning speed.

• Type: Conference
• Year: 2005
• Where: CEC
• Authors: Larry Bull, Matthew Studley, Anthony J. Bagnall, Ian Whittley
• Keywords: Accuracybased Learning Classifier, Artificial Intelligence, CEC 2005, Learning Classifier Systems, Rule Migration Mechanism