Open AccessLearning SEC<sub>p</sub> Languages from Only Positive Data
Author(s) -
Leonor Becerra-Bonache
Publication year - 2018
Publication title -
triangle
Language(s) - English
Resource type - Journals
ISSN - 2013-939X
DOI - 10.17345/triangle8.1-18
Subject(s) - learnability , grammar induction , inference , computer science , artificial intelligence , linguistics , natural language processing , relevance (law) , rule based machine translation , philosophy , political science , law
The eld of Grammatical Inference provides a good theoretical framework for investigating a learning process. Formal results in this eld can be relevant to the question of rst language acquisition. However, Grammatical Inference studies have been focused mainly on mathematical aspects, and have not exploited the linguistic relevance of their results. With this paper, we try to enrich Grammatical Inference studies with ideas from Linguistics. We propose a non-classical mechanism that has relevant linguistic and computational properties, and we study its learnability from positive data.