Artificial Cognitive Systems2018VT
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Course plan
No of lectures
Approximately 8 lectures/seminars.
Recommended for
PhD students (and possibly masters students) in cognitive science and computer science. The course is suitable for cognitive scientists who want to get deeper insights into building artificial cognitive systems, AND for computer scientists who want to get insights into a cognitive-science-based approach to artificial intelligence. The course could also be interesting for PhD students in psychology, neuroscience, philosophy or other areas overlapping with the cognitive sciences.
The course was last given
2016 HT
Goals
To provide an overview of different approaches to building artificial cognitive systems as well as current research issues.
Prerequisites
Some background in the cognitive sciences and/or artificial intelligence.
Organization
Course consists mostly of seminars and student presentations.
Contents
The nature of cognition. Paradigms of cognitive science. Cognitive architectures. Autonomy. Embodiment. Development and learning. Memory and prospection. Knowledge and representation. Social cognition and interaction. Distributed cognitive systems.
Literature
D Vernon (2014). Artificial Cognitive Systems: A Primer. MIT Press.
+ recent research articles
Lecturers
Tom Ziemke
Examiner
Tom Ziemke
Examination
Mandatory seminar participation, presentations and coursework.
Credit
6 hp
Comments
The course has been discussed briefly with Nahid as a possible CUGS course, but
as far as I know no decision has been taken about whether or not it should be
given. That's why I'm submitting it here as a proposal.
Course content can be adapted to some degree to the composition/backgrounds of
the students taking it.
Page responsible: Director of Graduate Studies