Abstract
We recall briefly in this paper the formal theory of regular grammatical inference from positive and negative samples of the language to be learned. We state this problem as a search toward an optimal element in a boolean lattice built from the positive information. We explain how a genetic search technique may be applied to this problem and we introduce a new set of genetic operators. In view of limiting the increasing complexity as the sample size grows, we propose a semi-incremental procedure. Finally, an experimental protocol to assess the performance of a regular inference technique is detailed and comparative results are given.
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Dupont, P. (1994). Regular grammatical inference from positive and negative samples by genetic search: the GIG method. In: Carrasco, R.C., Oncina, J. (eds) Grammatical Inference and Applications. ICGI 1994. Lecture Notes in Computer Science, vol 862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58473-0_152
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DOI: https://doi.org/10.1007/3-540-58473-0_152
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