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This paper focuses on a subfield of machine learning, the so-called grammatical inference. A a new framework of grammatical inference motivated by the process of acquiring natural language is suggested. The final goal of this research is to improve techniques in machine learning by using as a model natural language acquisition. We claim that the simulation of the process of acquiring a natural language could improve grammatical inference techniques and this improvement could have important implications in the field of human language technologies.
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