  Modern Learning Classifier Systems can be characterized by their use of rule
accuracy as the utility metric for the search algorithm(s) discovering useful
rules. Such searching typically takes place within the restricted space of
co-active rules for efficiency. This paper gives an historical overview of the
evolution of such systems up to XCS, and then some of the subsequent
developments of XCS to different types of learning.
