MDL-Based Fitness Functions for Learning Parsimonious Programs

Byoung-Tak Zhang and Heinz Muhlenbein

In this paper we use a Bayesian model-comparison method to develop a framework in which a class of fitness measures is introduced for dealing with problems of parsimony based on the minimum description length (MDL) principle (Rissanen 1986). We then scribe an adaptive technique for putting this fitness function into practice.


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