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CS62S: Expert Systems

CS62S: Expert Systems. Based on: The Engineering of Knowledge-based Systems: Theory and Practice A. J. Gonzalez and D. D. Dankel. Introduction to Knowledge-based Systems. General problem solving knowledge Intelligent program Inference engine Knowledge base Data / Fact base

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CS62S: Expert Systems

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  1. CS62S: Expert Systems Based on: The Engineering of Knowledge-based Systems: Theory and Practice A. J. Gonzalez and D. D. Dankel

  2. Introduction to Knowledge-based Systems • General problem solving knowledge • Intelligent program • Inference engine • Knowledge base • Data / Fact base • Separation of knowledge from its use • For a new problem domain – change knowledge base

  3. Knowledge Representation • Logic • Rules • Associative (semantic) networks • Frames • Objects

  4. Traditional Computer Programming • Structured sequence of steps • Algorithm • Finite amount of time

  5. Search – alternative to algorithmic solution • Path connecting problem to the solution • Problem space • Procedurally defined • Network • Tree • Solution space (problem space examined)

  6. Search Methods • Random • Blind • Directed

  7. Search Types • Depth-first • Breath-first • Beam • Hill-climbing • Branch and bound • Best-first • A* (best-first and branch and bound)

  8. Heuristics vs. algorithm • Specific knowledge • Rule of thumb • Prior knowledge • Expertise • Timely solution • Estimation

  9. Gonzalez and Dankel describes knowledge-based systems as: “A computerized system that uses knowledge about some domain to arrive at a solution to a problem from that domain. This solution is essentially the same as that concluded by a person knowledgeable about the domain of the problem when confronted with the same problem“

  10. Expert systems • Separation of knowledge from how it is used • Use of highly specific domain knowledge • Heuristic rather than algorithms

  11. MYCIN Used to diagnose blood disorder Incorporates all three elements

  12. Types of expertise • Associational The internal workings of a system are not understood. The behaviour is used to solve problems

  13. Motor skills expertise Practice makes perfect (sports, physical tasks, etc)

  14. Theoretical expertise The internal workings of a device or system are well understood. The expert can solve problems never seen before.

  15. Advantages of Expert Systems • Wide distribution of scarce expertise • Ease of modification • Consistency of answers • Perpetual accessibility • Preservation of expertise • Solution of Problem involving incomplete data • Explanation of solution

  16. Disadvantages • Answers may not always be correct • Knowledge limited to the domain of expertise • Lack of common sense

  17. Expert systems architecture • User • Knowledge engineer • Tool builder

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