Computational Simulations of Language

Uitgebreide vaknaam	Computational Simulations of Language
Leerdoelen	At the end of the course, students should be able to talk about the history of computational simulations of language learning, and understand the differences between learning models, recognizing the benefits as well as the shortcoming. Students should also be able to set up computational simulation of a statistical learning experiment when presented with experimental data.
Omschrijving	This course introduces students to implicit statistical learning in language, and computational simulations of that learning. The course also gives an introduction to the debate between empirical and rational models of language. Topics covered include: 1. Connectionist models of language: their rationale, achievements and drawbacks 2. The debate between connectionism and symbolic models of cognition 3. Psychological proposals of learning applied to language, including naive discriminate learning 4. The similarities and differences in learning progression modelled with recurrent neural networks compared to modelling with naive discriminate learning. 5. Insight into what statistical language patterns can be learned implicitly by infants and adults, what statistical patterns are challenging, and what this tells us about human cognition Student evaluations are based on the results of three computer labs. In these labs students: • recreate and investigate the behavior of classic connectionist models. • recreate and investigate the behavior of naïve discriminate learning • model experimental data that illustrates statistical learning in humans, comparing naïve discriminate learning and compare these models to neural network models • evaluate the results of the simulations compared to results from human participants The course gives a gentle introduction into simple neural networks and naïve discriminant learning. Students are not expected to have previous experience with neural networks or other machine learning methods in order to do the course.
Uren per week
Onderwijsvorm	Hoorcollege (LC), Practisch werk (PRC) (Introductory lecture, homework and lab sessions)
Toetsvorm	Opdracht (AST)
Vaksoort	master
Coördinator	Dr. J.K. Spenader
Docent(en)	Dr. J.K. Spenader
Entreevoorwaarden	Mandatory: No prior knowledge is assumed. Please note that the student is expected to have a relevant BSc degree.
Opmerkingen
Opgenomen in	Opleiding Jaar Periode Type MSc Artificial Intelligence  (C - Elective Course Units) - semester II a keuze MSc Computational Cognitive Science  (B - Mandatory Course Units Cognitive Language Modelling) 1 semester II a verplicht CLM MSc Computational Cognitive Science  (C - Elective Course Units) - semester II a keuze MSc Courses for Exchange Students: AI - Computing Science - Mathematics - semester II a ReMa Taalwetenschappen / Linguistics  (ReMa Language and Communication Technologies (LCT); Erasmus Mundus) 1 semester II a keuze