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  1. Editors' Review and Introduction: Learning Grammatical Structures: Developmental, Cross‐Species, and Computational Approaches.Carel ten Cate, Judit Gervain, Clara C. Levelt, Christopher I. Petkov & Willem Zuidema - 2020 - Topics in Cognitive Science 12 (3):804-814.
    Artificial grammar learning (AGL) is used to study how human adults, infants, animals or machines learn various sorts of rules defined over sounds or visual items. Ten Cate et al. introduce the topic and provide a critical synthesis of this important interdisciplinary area of research. They identify the questions that remain open and the challenges that lie ahead, and argue that the limits of human, animal and machine learning abilities have yet to be found.
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  • Structured Sequence Learning: Animal Abilities, Cognitive Operations, and Language Evolution.Christopher I. Petkov & Carel ten Cate - 2020 - Topics in Cognitive Science 12 (3):828-842.
    Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature in (...)
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