Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
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Computational approaches to learning aspects of language typically reduce the problem to learning syntax alone, or learning a lexicon alone. These simplifications have led to disconnected solutions and some unreasonable assumptions about inputs to their algorithms. In this paper, we present an approach that exploits a grammar learning algorithm to learn its own alphabet, or lexicon. We present empirical results and categorize the successes and types of errors lexical acquisition approaches encounter.