Bill Keller, Rudi Lutz
A genetic algorithm for inferring stochastic context-free grammars from finite language samples is described. Solutions to the inference problem are evolved by optimizing the parameters of a covering grammar for a given language sample. We describe a number of experiments in learning grammars for a range of formal languages. The results of these experiments are encouraging and compare very favourably with other approaches to stochastic grammatical inference.
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