This work suggests two ways of looking at Michigan classifier systems; as Genetic Algorithm-based systems, and as Reinforcement Learning-based systems, and argues that the former is more suitable for traditional strength-based systems while the latter is more suitable for accuracy-based XCS. The dissociation of the Genetic Algorithm from policy determination in XCS is noted, and the two types of Michigan classifier system are contrasted with Pittsburgh systems.
|Translated title of the contribution||Two Views of Classifier Systems|
|Title of host publication||Advances in Learning Classifier Systems|
|Publication status||Published - 2002|
Bibliographical noteOther page information: 74-87
Other identifier: 1000647