Learning SCFGs from Corpora by a Genetic Algorithm

  • B. Keller
  • R. Lutz
Conference paper


A genetic algorithm for inferring stochastic context-free grammars from finite language samples is described. Solutions to the inference problem are found 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.


Genetic Algorithm Terminal Symbol Grammatical Inference Syntactic Pattern Recognition Threshold Fitness 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Wien 1998

Authors and Affiliations

  • B. Keller
    • 1
  • R. Lutz
    • 1
  1. 1.School of Cognitive and Computing SciencesThe University of SussexBrightonUK

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