| Ivo Düntsch | |
http://www.cosc.brocku.ca/~duentsch/ |
| Computer Science Department |
|
|
| Brock University | Ph: (+1) (905) 688 5550, ext 3090 | |
| St Catharines, Ontario, L2S 3A1 | Fax: (+1) (905) 688 3255 |
|
|
Objectives |
On completion of this course you should be able to
Demonstrate familiarity with
Basic issues of artifical intelligence and data modelling, including the possibilities and limits of quasi-intelligent systems,
Problem solving techniques,
Principles of probability and methods of uncertainty handling,
Formal foundations of knowledge representation and rule based systems.
|
|
Content |
The course will cover the areas listed below; this is a tentative programme, and may be changed.
| Topic 1 | Data models |
| Topic 2 | Strategies
of
problem solving a la Polya |
| Topic 3 | Uncertainty and principles of probability |
| Topic 4 | Bayesian reasoning |
| Topic 5 | Formal systems and grammars |
| Topic 6 | Propositional logics |
| Topic 7 | Rough set data analysis and Knowledge structures |
|
|
Course material |
|
There will be no prescribed textbook. A full set of lecture notes will be made available. |
|
|
|
Administrative details |
|
Lecture times and place: |
Mon, Wed 12.30 - 14.00 MCA241, tentative schedule |
|
Office hours: |
By appointment |
|
Assessment: |
Two class tests (30% each) and a 30 min oral examination at the end of the course (40%) (tentative) |
