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GECCO
2007
Springer

MILCS: a mutual information learning classifier system

9 years 5 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifically designed for supervised learning. MILCS’s design draws on an analogy to the structural learning approach of cascade correlation networks. We present preliminary results, and contrast them to results from XCS. We discuss the explanatory power of the resulting rule sets, and introduce a new technique for visualizing explanatory power. Final comments include future directions for this research, including investigations in neural networks and other systems. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning: Induction General Terms Algorithms Keywords Learning classifier systems, evolutionary computation, structural learning, supervised learning, cascade correlation, information theory, mutual information, visualization, explanatory power, rule learning.
Robert Elliott Smith, Max Kun Jiang
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Robert Elliott Smith, Max Kun Jiang
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