Level
KI.B3
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Prerequisites
Basic Knowledge of AI (e.g. Introduction artificial intelligence [BKI120]
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Objectives
The course aims to provide participants with insight into a number of specific aspects that play a role in developing knowledge-intensive systems. The focus is on knowledge modelling and problem solving methods, not so much on implementation and programming techniques. The main developments in a number of relevant topics are discussed and where possible exemplified by existing systems.
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Contents
After a general introduction, the following topics are discussed: - the meaning of symbols, symbol systems, representations and knowledge;
- analytic approaches to knowledge system development;
- handling aspects of time, space, uncertainty and vagueness;
- formal models of different problem types and examples of classical knowledge systems for those problem types;
- advanced techniques such as bayesian networks, machine learning, truth maintenance systems.
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Literature
- Stefik, M. (1995). Introduction to knowledge systems. Morgan Kaufman. ISBN 1-55860-166-X
- supplementary articles
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Teaching methods
Discussion sessions that are prepared and introduced in turns by one of the participants.
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Information
dr.P.A.Kamsteeg, telf. 3612682, email:
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Coördinerend docent
dr. P.A. Kamsteeg
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Exam
Twee deeltentamens (open vragen, gesloten boek), schriftelijke inleidingen
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Exam information
Type of exam: Two partial tests consisting of open question (closed book), introduction texts.
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Enrollment verplicht via KISS/TIS tot 2 werkdagen voor aanvang; deze inschrijving geldt tevens voor het tentamen |
Extra enrollment information
Compulsory through KISS/TIS until 2 office days before start; this registration is also valid for the tests.
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Extra information
The master course Knowledge acquisition for expert systems (MKI33) expands on this course in the form of practical assignments to acquire the necessary knowledge for an expert system.
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