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
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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.