URKS Uncertainty Reasoning in Knowledge Systems

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URKSUncertainty Reasoningin Knowledge Systems
H. Bruyninckx M. Nuttin D. De Schreye
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Course overview

• Introduction on uncertainty in A.I.
• Motivation - examples - some basic concepts
• D. De Schreye (1 session)?

• Probability concepts, techniques and systems
• Bayesian theory and approach
• H. Bruyninckx (6 sessions)?
• Fuzzy concepts, techniques and systems
• Zadeh theory and approach/possibility theory
• M. Nuttin (6 sessions)?

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Practical sessions

• 4 practical sessions of 2.5 hours

• 2 sessions on probability examples
• 2 sessions on fuzzy examples
• examination exercises related to lab-sessions
• (1/2 of points)?
• open book
• remainder written theory exam.
• closed book

Http//www.cs.kuleuven.ac.be/dannyd/URKS
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Study of relation between imprecise language and
frequency
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Going Fuzzy for a few minutes.

• Examples of Fuzzy statements

• The motor is running very hot.
• Tom is a very tall guy.
• Electric cars are not very fast.
• High-performance drives require very rapid
  dynamics and precise regulation.
• Leuven is quite a short distance from Brussels.
• Leuven is a beautiful city.
• The maximum range of an electronic vehicle is
  short.

• If short means 300 km or less, would 301 km be
  long ?

• Want to express to what degree a property holds.

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And much, MUCH MORE ... in the coming lessons.