Abstract
This paper focuses on three areas: machine learning, agent technologies and formal language theory. Our goal is to show how the interrelation among agents, learning and formal languages can contribute to the solution of a challenging problem: the explanation of how natural language is acquired and processed. Linguistic contributions of the intersection between machine learning and formal language theory –through the field of grammatical inference– are reviewed. Agent-based formal language models as colonies, grammar systems and eco-grammar systems have been applied to different natural language issues. We review the most relevant applications of these models.
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Becerra-Bonache, L., Jiménez-López, M.D. (2015). Learning, Agents, and Formal Languages: Linguistic Applications of Interdisciplinary Fields. In: Bajo, J., et al. Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-319-19629-9_5
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DOI: https://doi.org/10.1007/978-3-319-19629-9_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19628-2
Online ISBN: 978-3-319-19629-9
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