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Artificial Intelligence ,[object Object],[object Object]
Knowledge-based systems /57
Introduction, or what is knowledge? ,[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
Knowledge Sources ,[object Object],[object Object],[object Object],[object Object],[object Object]
Knowledge Levels   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Scope of Knowledge   ,[object Object],[object Object]
Domain Expert   ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Major Categories of Knowledge  ,[object Object],[object Object],[object Object]
Declarative Knowledge  ,[object Object],[object Object],[object Object],[object Object]
Procedural Knowledge ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
Meta knowledge  ,[object Object],[object Object],[object Object],[object Object],[object Object]
What’s in the knowledge base? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Knowledge-based systems ,[object Object],[object Object],[object Object]
Components of KBS ,[object Object],Input output unit  Inference control unit Knowledge base
Structure and characteristics  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],/57 AI programs Knowledge-based systems Expert systems
The Knowledge Hierarchy meta- knowledge knowledge information data noise large volume, low value, usually no meaning/ context lower volume, higher value, with context and associated meanings understanding of a domain, can be applied to solve problems knowledge on knowledge (e.g how/when to apply) may contain irrelevant items which obscure data management information systems knowledge- based systems databases, transaction systems
Different type of knowledge base system
What is Knowledge Engineering? ,[object Object],[object Object],[object Object],[object Object],[object Object]
knowledge Engineering ,[object Object]
Knowledge Engineering  ,[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Knowledge Engineering ,[object Object],[object Object],[object Object],[object Object],[object Object]
Views of knowledge engineering ,[object Object],[object Object],[object Object]
Knowledge Engineering Process Activities ,[object Object],[object Object],[object Object],[object Object],[object Object]
Knowledge Engineering Process  Knowledge validation (test cases) Knowledge Representation Knowledge Acquisition Encoding Inferencing Sources of knowledge (experts, others) Explanation justification Knowledge base
Knowledge Engineering in a Nutshell human expert knowledge engineer knowledge base (in ES) explicit knowledge dialog knowledge refinement
Phases of KE ,[object Object]
Knowledge Engineering Principles ,[object Object],[object Object],[object Object],[object Object],[object Object]
The main players in the development team
Intelligent System A System can be constructed as a intelligence system if it has four major techniques of knowledge representation. 1.Logic The logic is a formal procedure because of which implications are created from the set of known facts. 2.Production Systems The production systems studies the new facts and the known facts and finds the desired conclusion. 3.Semantic networks It is a network of symbols that describe relationship between elements of knowledge 4.Frames These are the data structures which consists of expectations for a given situation.
[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Elements of a Representation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
Terminology ,[object Object],[object Object]
[object Object],[object Object]
Different levels of knowledge representation Mental Image Written Text Magnetic Spots Binary Numbers Character Strings
How Knowledge Representation Works ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How knowledge representations are used in cognitive models ,[object Object],[object Object],Knowledge Base Inference Mechanism(s) Learning Mechanism(s) Examples, Statements Questions, requests Answers, analyses
 
Knowledge acquisition ,[object Object]
 
Issues in Knowledge Acquisition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object]
KA Techniques … ,[object Object],[object Object],[object Object],[object Object]
Knowledge Acquisition Methods:  An Overview   ,[object Object],[object Object],[object Object]
Manual Methods Structured Around   Interviews   ,[object Object],[object Object],[object Object],[object Object],[object Object]
Manual Methods of knowledge Acquisition Elicitation Knowledge base Documented knowledge Experts  Coding Knowledge engineer
Semiautomatic Methods   ,[object Object],[object Object]
Expert-Driven  Knowledge Acquisition Knowledge base Knowledge engineer Expert  Coding Computer-aided (interactive) interviewing
Automatic Methods ,[object Object],[object Object]
Induction-Driven Knowledge Acquisition Knowledge base Case histories and examples Induction system
 
 
 
 
Knowledge Acquisition Difficulties ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Other Reasons
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Advantages of KBSs and ESs ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],/57
Disadvantages of KBSs and ESs ,[object Object],[object Object],[object Object],[object Object],/57
[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
[object Object],[object Object],[object Object]

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Artificial Intelligence

  • 1.
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  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18. The Knowledge Hierarchy meta- knowledge knowledge information data noise large volume, low value, usually no meaning/ context lower volume, higher value, with context and associated meanings understanding of a domain, can be applied to solve problems knowledge on knowledge (e.g how/when to apply) may contain irrelevant items which obscure data management information systems knowledge- based systems databases, transaction systems
  • 19. Different type of knowledge base system
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26.
  • 27. Knowledge Engineering Process Knowledge validation (test cases) Knowledge Representation Knowledge Acquisition Encoding Inferencing Sources of knowledge (experts, others) Explanation justification Knowledge base
  • 28. Knowledge Engineering in a Nutshell human expert knowledge engineer knowledge base (in ES) explicit knowledge dialog knowledge refinement
  • 29.
  • 30.
  • 31. The main players in the development team
  • 32. Intelligent System A System can be constructed as a intelligence system if it has four major techniques of knowledge representation. 1.Logic The logic is a formal procedure because of which implications are created from the set of known facts. 2.Production Systems The production systems studies the new facts and the known facts and finds the desired conclusion. 3.Semantic networks It is a network of symbols that describe relationship between elements of knowledge 4.Frames These are the data structures which consists of expectations for a given situation.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39. Different levels of knowledge representation Mental Image Written Text Magnetic Spots Binary Numbers Character Strings
  • 40.
  • 41.
  • 42.  
  • 43.
  • 44.  
  • 45.
  • 46.
  • 47.
  • 48.
  • 49.
  • 50.
  • 51. Manual Methods of knowledge Acquisition Elicitation Knowledge base Documented knowledge Experts Coding Knowledge engineer
  • 52.
  • 53. Expert-Driven Knowledge Acquisition Knowledge base Knowledge engineer Expert Coding Computer-aided (interactive) interviewing
  • 54.
  • 55. Induction-Driven Knowledge Acquisition Knowledge base Case histories and examples Induction system
  • 56.  
  • 57.  
  • 58.  
  • 59.  
  • 60.
  • 61.
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