Abstract
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 |
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Original language | English |
Title of host publication | Advances in Learning Classifier Systems |
Publisher | Springer |
Volume | 2321 |
ISBN (Print) | 3540437932 |
Publication status | Published - 2002 |
Bibliographical note
Other page information: 74-87Other identifier: 1000647