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An Evolutionary Approach to Concept Learning with Structured Data

Claire J. Kennedy, Christophe Giraud-Carrier, An Evolutionary Approach to Concept Learning with Structured Data. Proceedings of the fourth International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 1–6. April 1999. PDF, 33 Kbytes.

Abstract

This paper details the implementation of a strongly-typed evolutionary programming system (STEPS) and its application to concept learning from highly-structured examples. STEPS evolves concept descriptions in the form of program trees. Predictive accuracy is used as the fitness function to be optimised through genetic operations. Empirical results with representative applications demonstrate promise.

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