Self-assessment questions

  • What is reasoning and how reasoning can be performed when there is data uncertainty? 
  • Explain the differences between reasoning using the Bayesian rule and using certainty factors. Give an example of rule representation in an AI system that uses Bayesian probabilities and an example that uses certainty factors.
  • Discuss ways uncertainty is introduced when AI systems are developed in practice.
  • What are the differences between fuzzy sets and crisp sets? Explain by means of an example. 
  • Explain by means of an example what a linguistic variable is. Define fuzzy sets for that variable, draw their figures, and define their universe of discourse. 
  • Explain what a fuzzy rule is and what the difference between classical and fuzzy rules is.
  • Define two fuzzy sets and calculate their intersection (min) and union (max).
  • Explain how one could adjust the range of each fuzzy set.
  • What is defuzzification? 
  • Describe two popular defuzzification methods. Explain graphically, giving an example, how one can determine the final output of a fuzzy system using these methods.


Last modified: Wednesday, 22 January 2020, 7:13 PM