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A computational model of the usage-based acquisition of abstract constructions and grammatical categories.

This project starts from an important insight gained from usage-based theories of language acquisition, namely that the ability of children to learn language is based on 2 general cognitive capacities: intention reading and pattern finding. Intention reading refers to the capacity of children to share attention, recognise gestures and understand the communicative intentions of their interlocutors. Pattern finding refers to the ability of children to recognise similarities and differences in their sensory-motor experiences and to use this ability for schema formation. Together, intention reading and pattern finding provide thus the necessary mechanisms for generalising across different communicative interactions, thereby constructing abstract schemata that represent the linguistic knowledge of a language user. While there is ample empirical evidence to support this hypothesis, there exist to date no faithful mechanistic models of the processes involved in acquiring such abstract schemata. The objective of this research project aims to fill this gap by providing a fully operational mechanistic model of the usage-based acquisition of abstract schemata (constructions), along with a system of grammatical categories that captures how these schemata interact with each other.

Date:1 Sep 2021 →  Today
Keywords:usage-based language acquisition, generalization, abstract constructions, grammatical categories, computational models, artificial agents, AI, construction grammar
Disciplines:Computational linguistics, Adaptive agents and intelligent robotics, Evolutionary linguistics
Project type:PhD project