| Learning Classifier System |
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| CATEGORIES ABOUT LEARNING CLASSIFIER SYSTEM | |
| evolutionary algorithms | |
| machine learning | |
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Learning classifier systems can be split into two types depending upon where the genetic algorithm acts. A Pittsburgh-type LCS has a population of separate rule sets, where the genetic algorithm recombines and reproduces the best of these rule sets. In a Michigan-style LCS there is only a single population and the algorithm's action focuses on selecting the best classifiers within that ruleset. Michigan-style LCSs have two main types of reinforcement learning, fitness sharing (ZCS) and accuracy-based ('''XCS'''). Initially the classifiers or rules were , but recent research has focused on improving this representation. This has been achieved by using populations of Neural Networks and other methods. Learning classifier systems are not well-defined Mathematically and doing so remains an area of active research. Despite this, they have been successfully applied in many problem domains. EXTERNAL LINKS |
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