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Lecture Notes in Computer Science
Grammatical inference consists in learning formal grammars for unknown languages when given learning data. Classically this data is raw: strings that belong to the language or that do not. We present in this paper the possibility of learning when presented with additional information such as the knowledge that the hidden language belongs to some known language, or that the strings are typed, or that specific patterns have to/can appear in the strings. We propose a general setting to deal withdoi:10.1007/3-540-45790-9_13 fatcat:adbjrahojfejxieqmglom6vnay