KOGS536 Cognitive Modeling (5 cr)
Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2020-2021, 2021-2022, 2022-2023
Description
Content
This course explores the principles of cognition and intelligence in human beings and machines, focusing on how to build computational models that, in essence, think and act like people. The course reviews existing frameworks for such models, studies model development within one particular framework, and discusses how models can be employed in real-world domains.
Completion methods
Independent study of the video lectures is expected. Demos and homework will build on topics discussed in the videos. The course grade will be determined from a final exam at the end of the course.
Learning outcomes
The course objectives are to: review existing frameworks for modeling human cognition, including broad categories of symbolic, connectionist, and hybrid frameworks; study a particular framework in the context of illustrative psychological domains (e.g., memory, attention, language); build running simulation models of cognition and performance using this framework; explore how such models can be employed in real-world application domains such as intelligent tutoring and driving. As learning outcomes, students completing this course should be able to: describe existing frameworks for modeling human cognition; use an existing computational framework to build running simulation models of cognition and performance; describe how such models can be employed in real-world application domains.
Study materials
There is no assigned textbook for this course. Readings will come from several sources including academic papers and electronic resources (e.g., web tutorials).
Completion methods
Method 1
Select all marked parts
Parts of the completion methods
x
Teaching (5 cr)
Type:
Participation in teaching
Grading scale:
0-5
Language:
English