Journal article
Editors' Review and Introduction: Learning Grammatical Structures: Developmental, Cross-Species, and Computational Approaches
Topics in cognitive science, Vol.12(3), pp.804-814
07/01/2020
DOI: 10.1111/tops.12493
PMID: 32134565
Abstract
Human languages all have a grammar, that is, rules that determine how symbols in a language can be combined to create complex meaningful expressions. Despite decades of research, the evolutionary, developmental, cognitive, and computational bases of grammatical abilities are still not fully understood. "Artificial Grammar Learning" (AGL) studies provide important insights into how rules and structured sequences are learned, the relevance of these processes to language in humans, and whether the cognitive systems involved are shared with other animals. AGL tasks can be used to study how human adults, infants, animals, or machines learn artificial grammars of various sorts, consisting of rules defined typically over syllables, sounds, or visual items. In this introduction, we distill some lessons from the nine other papers in this special issue, which review the advances made from this growing body of literature. We provide a critical synthesis, identify the questions that remain open, and recognize the challenges that lie ahead. A key observation across the disciplines is that the limits of human, animal, and machine capabilities have yet to be found. Thus, this interdisciplinary area of research firmly rooted in the cognitive sciences has unearthed exciting new questions and venues for research, along the way fostering impactful collaborations between traditionally disconnected disciplines that are breaking scientific ground.
Details
- Title: Subtitle
- Editors' Review and Introduction: Learning Grammatical Structures: Developmental, Cross-Species, and Computational Approaches
- Creators
- Carel ten Cate - Leiden UniversityJudit Gervain - CognIT (Norway)Clara C. Levelt - Leiden UniversityChristopher I. Petkov - Newcastle UniversityWillem Zuidema - University of Amsterdam
- Resource Type
- Journal article
- Publication Details
- Topics in cognitive science, Vol.12(3), pp.804-814
- DOI
- 10.1111/tops.12493
- PMID
- 32134565
- NLM abbreviation
- Top Cogn Sci
- ISSN
- 1756-8757
- eISSN
- 1756-8765
- Publisher
- Wiley
- Number of pages
- 11
- Grant note
- Lorentz Center (Leiden, Netherlands) NIAS Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS-Amsterdam, Netherlands); Netherlands Government BB/J009849/1 / BBSRC; UK Research & Innovation (UKRI); Biotechnology and Biological Sciences Research Council (BBSRC)
- Language
- English
- Date published
- 07/01/2020
- Academic Unit
- Iowa Neuroscience Institute; Neurosurgery; Otolaryngology
- Record Identifier
- 9984360132502771
Metrics
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