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Knowledge & Inexact Reasoning ,[object Object],[object Object],[object Object],[object Object],[object Object]
Inexact Reasoning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Forms of Inexact Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Inexact Knowledge - Example ,[object Object],default -   A wants to take a bus belief, (un)certainty  - it's the neighbor B probability, default, uncertainty -   the neighbor goes home by car  default -   A wants to get a lift  default -   A wants to go home  Q:  Which forms of inexact knowledge and reasoning are involved here?
Examples of Inexact Knowledge ,[object Object],Fuzzy   -  a few hundred yards define a mapping from " #hundreds " to ' few ', ' many ', ... not uncertain or incomplete but graded, vague Probabilistic   -  the neighbor usually goes by car probability based on measure of how often he takes car;  calculates  always   p(F) = 1 - p( ¬F) Belief   -  it's his next-door neighbor B   "reasoned assumption", assumed to be true Default   -  A wants to take a bus   assumption based on commonsense knowledge
Dealing with Inexact Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Uncertainty and Rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
Figure 5.1 Major Uncertainties in Rule-Based Expert Systems
Figure 5.2 Uncertainties in Individual Rules
Figure 5.3 Uncertainty Associated with the Compatibilities of Rules
Figure 5.4 Uncertainty Associated with Conflict Resolution
Goal of Knowledge Engineer ,[object Object],[object Object],[object Object]
Verification vs. Validation ,[object Object],[object Object],[object Object],[object Object]
Ad Hoc Methods ,[object Object],[object Object],[object Object]
Sources of Uncertainty ,[object Object],[object Object]
Uncertainty in Conflict Resolution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Uncertainty ,[object Object],[object Object],[object Object]
Uncertainty ,[object Object],[object Object],[object Object]
Certainty Factors ,[object Object]
Difficulties with Bayesian Method ,[object Object],[object Object],[object Object]
Belief and Disbelief ,[object Object],[object Object],[object Object],[object Object]
Belief and Disbelief ,[object Object],[object Object],[object Object]
Likelihood of Belief / Disbelief ,[object Object],[object Object],[object Object]
Measures of Belief and Disbelief ,[object Object],[object Object],[object Object],[object Object]
Certainty Factor Values ,[object Object],[object Object],[object Object],[object Object]
Threshold Values ,[object Object],[object Object],[object Object],[object Object]
Difficulties with Certainty Factors ,[object Object],[object Object],[object Object]
Dempster-Shafer Theory ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object]
Dempster-Shafer ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Approximate Reasoning ,[object Object],[object Object],[object Object]
Fuzzy Sets and Natural Language ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fuzzy Sets and Natural Language  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fuzzy Set Operations ,[object Object],[object Object]
Fuzzy Set Operations  Set equality Set Complement Set Containment Proper Subset Set Union Set Intersection Set Product Power of a Set Probabilistic Sum Bounded Sum Bounded Product Bounded Difference Concentration Dilation Intensification Normalization
Fuzzy Relations ,[object Object],[object Object],[object Object],[object Object]
Fuzzy Relations ,[object Object],[object Object],[object Object]
Table 5.7 Some Applications of Fuzzy Theory
Table 5.8 Some Fuzzy Terms of Natural Language
Linguistic Variables ,[object Object],[object Object],[object Object]
Extension Principle ,[object Object],[object Object],[object Object]
Fuzzy Logic ,[object Object],[object Object]
Possibility and Probability and Fuzzy Logic ,[object Object],[object Object]
Translation Rules ,[object Object],[object Object],[object Object],[object Object],[object Object]
State of Uncertainty Commercial Applications ,[object Object],[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object]

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Inexact reasoning

  • 1.  
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7.
  • 8.
  • 9. Figure 5.1 Major Uncertainties in Rule-Based Expert Systems
  • 10. Figure 5.2 Uncertainties in Individual Rules
  • 11. Figure 5.3 Uncertainty Associated with the Compatibilities of Rules
  • 12. Figure 5.4 Uncertainty Associated with Conflict Resolution
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27.
  • 28.
  • 29.
  • 30.
  • 31.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39.
  • 40.
  • 41.
  • 42.
  • 43.
  • 44. Fuzzy Set Operations Set equality Set Complement Set Containment Proper Subset Set Union Set Intersection Set Product Power of a Set Probabilistic Sum Bounded Sum Bounded Product Bounded Difference Concentration Dilation Intensification Normalization
  • 45.
  • 46.
  • 47. Table 5.7 Some Applications of Fuzzy Theory
  • 48. Table 5.8 Some Fuzzy Terms of Natural Language
  • 49.
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  • 56.