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
Publication statusPublished - 8 Nov 2018
Event30th Benelux Conference on Artificial Intelligence - BNAIC 2018 - Jheronimus Academy of Data Science, ‘s-Hertogenbosch, Netherlands
Duration: 8 Nov 20189 Nov 2018


Conference30th Benelux Conference on Artificial Intelligence - BNAIC 2018
Internet address

ID: 44322491