Usage-based learning of grammatical categories

Luc Steels, Paul Van Eecke, Katrien Beuls

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

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Abstract

Human languages use a wide range of grammatical categories to constrain which words or phrases can fill certain slots in grammatical patterns and to express additional meanings, such as tense or aspect, through morpho-syntactic means. These grammatical categories, which are most often language-specific and changing over time, are difficult to define and learn. This paper raises the question how these categories can be acquired and where they have come from. We explore a usage-based approach. This means that categories and grammatical constructions are selected and aligned by their success in language interactions. We report on a multi-agent experiment in which agents are endowed with mechanisms for understanding and producing utterances as well as mechanisms for expanding their inventories using a meta-level learning process based on pro- and anti-unification. We show that a categorial type network which has scores based on the success in a language interaction leads to the spontaneous formation of grammatical categories in tandem with the
formation of grammatical patterns.
Original languageEnglish
Title of host publicationBNAIC 2018 Preproceedings
Subtitle of host publication30th Benelux Conference on Artificial Intelligence - BNAIC 2018
Pages253-264
Number of pages12
Publication statusPublished - 9 Nov 2018

Publication series

NameBelgian/Netherlands Artificial Intelligence Conference
ISSN (Print)1568-7805

Keywords

  • cs.CL
  • cs.AI

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