SOW-MKI47
Trends in Artificial Intelligence
Course infoSchedule
Course moduleSOW-MKI47
Credits (ECTS)6
Category-
Language of instructionEnglish
Offered byRadboud University; Faculty of Social Sciences; Artificial Intelligence;
Lecturer(s)
Lecturer
prof. dr. M.A.J. van Gerven
Other course modules lecturer
Contactperson for the course
L.E.C. Jacques
Other course modules lecturer
Coordinator
dr. P.A. Kamsteeg
Other course modules lecturer
Examiner
dr. P.A. Kamsteeg
Other course modules lecturer
Lecturer
dr. J.H.P. Kwisthout
Other course modules lecturer
Academic year2018
Period
SEM1  (03/09/2018 to 03/02/2019)
Starting block
SEM1
Course mode
full-time
RemarksThis course is only available for students who started in 2017 or earlier.
Registration using OSIRISYes
Course open to students from other facultiesNo
Pre-registrationNo
Waiting listNo
Placement procedure-
Aims

This course aims to

  • familiarize the student with current research issues in Artificial Intelligence (e.g., as reported in journals like Artificial Intelligence, Journal of Experimental and Theoretical Artificial Intelligence, Pattern Recognition, Trends in Cognitive Science, Neural Networks, Connection Science)
  • promote a critical reflection on such issues,
  • stimulate the student to consider potentially interesting master thesis projects.
Content
A number of current, 'hot', research themes from the field of Artificial Intelligence (AI) will be addressed, both in the form of presentations giving a general overview, and through specific research papers. The themes will be diverse, each theme will be covered by a different AI-researcher who is a specialist in the field. Whenever possible, opposite or complementary views on the topic will be presented.

In total, 9 themes will be covered (which may vary per year). Each theme will be divided over two consecutive meetings. In the first meeting, an AI-researcher will present an introduction to the theme. For this first part, typically review articles from leading journals will be assigned as reading material. In the next meeting, one to three student groups will present a talk on the basis of an article from the primary literature, in which they will give a  critical reflection on that article. These articles are suggested by the lecturer responsible for the theme. 

Besides the scheduled meetings, each student is required to obtain 8 “colloquium points” by attending, and writing a short summary of scientific presentations or labmeetings outside the course meetings (e.g. Donders lectures). More details can be found in the course guide on Brightspace.
 
Levels
AI-MA

Test information
- Presentation
- Posted commentaries
- Research proposal (final assignment)
- Eight colloquium points

Prerequisites
A bachelor grade in the field of Artificial Intelligence, Computer Science, Cognitive Science or a related study programme.

Contact information
Dr. Paul Kamsteeg; p.kamsteeg@donders.ru.nl; 024-3612682

Required materials
Learning Management System (Brigthspace)
The reading assignments and the presentations of lecturers and students will be made available on the Brightspace site of the course.

Recommended materials
To be announced
Original articles (max. 30 pages per theme)

Instructional modes
Lecture

General
In total, 9 themes will be covered (which may vary per year). Each theme will be divided over two consecutive meetings. In the first meeting, an AI-researcher will present an introduction to the theme. For this first part, typically review articles from leading journals will be assigned as reading material.
In the next meeting, one to three student groups will present a talk on the basis of an article from the primary literature, in which they will give a critical reflection on that article.

Obtain colloquium points

General
Besides the scheduled meetings, each student is required to obtain 8 “colloquium points” by attending, and writing a short summary of scientific presentations or labmeetings outside the course meetings (e.g. Donders lectures). More details can be found in the course guide on Brightspace.

Presentation

General
Students that are not presenting a paper have to post a personal critical commentary (question or remark), pertaining to an issue of (one of) the papers presented, on the course’s Brightspace site before the presentation, so that the student presenting the talk will be able to take (at least some of) them into consideration during the talk.

Tests
Proposal
Test weight60
OpportunitiesBlock SEM1

Presentation
Test weight40
Test typePresentation
OpportunitiesBlock SEM1

Discussion
Test weight10
OpportunitiesBlock SEM1

Colloquium points
Test weight0
OpportunitiesBlock SEM1