| Ivo Düntsch | |
http://www.cosc.brocku.ca/~duentsch/ |
| Computer Science Department |
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| Brock University | Ph: (+1) (905) 688 5550, ext 3090 | |
| St Catharines, Ontario, L2S 3A1 | Fax: (+1) (905) 688 3255 |
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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.
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Content |
The course will cover some of the areas listed below; this is a tentative programme, and may be changed.
| Topic 1 | Data models |
| Topic 2 | Strategies of problem solving |
| Topic 3 | Uncertainty and principles of probability |
| Topic 4 | Bayesian reasoning and decision trees |
| Topic 5 | Grammars and formal systems |
| Topic 6 | Propositional logics |
| Topic 7 | Rough set data analysis and Knowledge structures |
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Course material |
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There will be no prescribed textbook. A full set of lecture notes will be made available. |
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Administrative details |
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Lecture times and place: |
Mon, Wed 15.30 - 17.00 PL 410 |
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Office hours: |
Tue, Thu 9.30 - 10.30 J313 |
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Assessment: |
Two class tests (25% each) and a 30 min oral examination at the end of the course (50%), Schedule for the final exam. |
