A brief history of learning classifier systems: from CS-1 to XCS and its variants
The direction set by Wilsons XCS is that 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 overview of the evolution of Learning Classifier Systems up to XCS, and then of some of the subsequent developments of Wilsons algorithm to different types of learning.
anticipation classification clustering function approximation reinforcement learning