Learning classifier systems

Martin V. Butz
2011 Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11  
Learning Classifier Systems use reinforcement learning, evolutionary computing and/or heuristics to develop adaptive systems. This paper extends the ZCS Learning Classifier System to improve its internal modelling capabilities. Initially, results are presented which show performance in a traditional reinforcement learning task incorporating lookahead within the rule structure. Then a mechanism for effective learning without external reward is examined which enables the simple learning system to
more » ... build a full map of the task. That is, ZCS is shown to learn under a latent learning scenario using the lookahead scheme. Its ability to form maps in reinforcement learning tasks is then considered.
doi:10.1145/2001858.2002121 dblp:conf/gecco/Butz11 fatcat:jozv6y67ufbolno63hm5mfxi2i