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Artificial Cognitive Systems

2018VT

Status Open for interest registrations
School Computer and Information Science (CIS)
Division
Owner Tom Ziemke

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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
Last updated: 2012-05-03