Prospectus

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Cognitive Modelling

Course
2021-2022

Admission requirements

Not applicable.

Description

Cognitive models define the algorithms underlying behavioral capacities such as learning and decision-making. For instance, reinforcement learning algorithms describe the adaptive process through which agents learn to predict the consequences of their behavior, through interactions with the environment.

Cognitive models are widely used in cognitive science, computer science and artificial intelligence to better understand the cognitive processes that give rise to intelligent behavior. Their components have been linked to specific processes in the brain, bridging from computation to functioning of the nervous system.
The principles of cognitive models have also been used as building blocks for various cognitive architectures, which aim to create a comprehensive computer program that can perform certain tasks (and explain human behavior).

This course will discuss and compare different approaches to cognitive modelling and cognitive architectures. Students will gain hands-on experience in implementing these models, and fitting them to data, through tutorials and assignments.

Course objectives

  • Students know the key paradigms and models currently employed in the field of reinforcement learning (based on a theoretical overview provided by the lectures);

  • Students know different cognitive architectures, and understand their differences and respective strengths and weaknesses;

  • Students can understand and program computational models, and fit them to experimental data;

  • Students can critically discuss current issues and future perspectives related to the reinforcement learning and cognitive modelling literature.

Timetable

Het meest recente rooster is te vinden op de Studenten-website:

Mode of instruction

The course consists of 14 lectures (including Q&A sessions) and 14 tutorials.

Assessment method

Grade:

  • programming assignment and report (100%)

Additional requirements:

  • finish 2 (out of 3) tutorial lab reports with a passing grade, as determined by in-class peer evaluation

Reading list

The booktitles and / or syllabi to be used in the course, where it can be purchased and how this literature should be studied beforehand.

Registration

Aanmelding voor vakken verloopt via uSis. Hiervoor is de uSis-code van het vak nodig, die te vinden zijn in de Studiegids. Meer info over het inschrijven voor vakken of tentamens is hier te vinden.

MyTimetable

In MyTimetable kun je alle vak- en opleidingsroosters vinden, waarmee jij je persoonlijke rooster kunt samenstellen. Onderwijsactiviteiten waarvoor je in uSis staat ingeschreven, worden automatisch in je rooster getoond. Daarnaast kun je My Timetable gemakkelijk koppelen aan een agenda-app op je telefoon en worden roosterwijzigingen automatisch in je agenda doorgevoerd; bovendien ontvang je desgewenst per e-mail een notificatie van de wijziging.

Vragen? Bekijk de video-instructie, lees de instructie of neem contact op met de ISSC helpdesk.

Brightspace

Inschrijving voor vakken verloopt via uSis. Wanneer je je hier inschrijft voor een bepaald vak krijg je automatisch ook toegang tot de omgeving van dit vak via Brightspace.

Voor meer informatie over Brightspace kun je op deze link klikken om de handleidingen van de universiteit te bekijken. Bij overige vragen of problemen kan contact opgenomen worden met de helpdesk van de universiteit Leiden.

Contact

Onderwijscoördinator Informatica, Riet Derogee.