Bachelor
Informatica
Informatiekunde
Kunstmatige intelligentie
Master
Computing Science
Game&Media Technology
Artifical Intelligence
Business Informatics

Website: | website containing additional information | |||||||||||||||

Course code: | INFOAN | |||||||||||||||

Credits: | 7.5 ECTS | |||||||||||||||

Period: | period 3 (week 6 through 16, i.e., 6-2-2012 through 20-4-2012; retake week 22)
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Timeslot: | D | |||||||||||||||

Participants: | up till now 31 subscriptions | |||||||||||||||

Schedule: | Official schedule representation can be found in Osiris | |||||||||||||||

Teachers: | Dit is een oud rooster!
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Exam: |
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Note: | No up-to-date course description available.Text below is from year 2010/2011 | |||||||||||||||

Contents: | Systems and programs are designed for many purposes and in many ways, but it's algorithms that make things work. Good algorithm design requires understanding and modelling an application, and subsequently studying and analyzing the computational features of the design. In this course we study a number of advanced techniques for efficient algorithm design, often at the hand of problems from networks and graphs. In many applications, networks and graphs are used as a model. Tyical examples are networks of roads, or electronic networks. In other applications, the graph model may be less obvious, but appears to be very useful, like for scheduling problems. In this course, we look to the translation of problem to network model, and we look to algorithmic problems and their solutions on networks and graphs. Some topics are: shortest paths, flow, matchings, triangulated graphs, treewidth, graph isomorphism, graph drawing, exact algorithms for fundamental graph problems, small world networks, facility location. | |||||||||||||||

Literature: | May change!Most literature will be handed out during the course. Recommended reading: - Algorithm Design. John Kleinberg, Eva Tardos, Pearson/Addision Wesley, 2005. ISBN 0-321-29535-8.
- Introduction to Algorithms. Cormen, Leiserson, Rivest, Stein. (Used in the
*Algorithms*course.)
not obligatory. Participation in classes is recommended: much is not covered in the books! | |||||||||||||||

Course form: | Lectures, two per week. Exercises. | |||||||||||||||

Exam form: | There are two tests and a number (8 - 10) exercise sets, and two exams. You must get an average of 6 for the exercise sets, and an average of 5 for the exams for a sufficient end note. The exercise sets count for 50 percent of the end note, and the two exams each for 25 percent. | |||||||||||||||

Minimum effort to qualify for 2nd chance exam: | To qualify for the retake exam, the grade of the original must be at least 4. |