Contents

• Introduction - rule-based systems
• Why are rule-based systems important?
• History
• What is a rule-based system?
• Expert systems
• Examples of expert systems
  • The ``Classical'' expert systems
  • Other expert systems
• How the inference engine works
  • Forward chaining
  • Backward chaining
  • Longer example of backward chaining
  • Longer example of forward chaining
  • More complicated inference methods
• Logic programming
  • **Inference in Prolog
• How expert systems explain themselves
• Where do the rules come from?
  • Rules by machine learning
• What's wrong with expert systems?
  • Maintaining large knowledge bases
  • Strategy and questioning
  • Explanations
  • Shallow reasoning
  • Lack of common sense, and restriction to narrow domains
  • No learning
  • Systems aren't adaptable
• Rule-based systems and some themes in AI
  • Backward chaining systems have goals and subgoals
  • Rule-based systems and good representations
  • Expert systems and productive laziness
  • Data-directed vs goal-directed
• About this document ...

AI lecture 3

Jocelyn Ireson-Paine