Representation - ARTIFICIAL INTELLIGENCE CHAPTER KNOWLEDGE...

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ARTIFICIAL INTELLIGENCE CHAPTER KNOWLEDGE REPRESENTATION
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RECALL: What is AI AI Techniques AI Applications
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DATA, INFORMATION AND KNOWLEDGE - Raw facts - Static - E.g. Liza, S’pore - Processed data - Has some meaning and purposes - E.g. Liza was born in S’pore - Derived from information - Stored in human brain - What we know
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DATA, INFORMATION AND KNOWLEDGE
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1. Introduction 2. Semantic Networks 3. Decision Tables 4. Decision Trees 5. Frames 6. Production Rules 7. Logic a. Propositional Logic b. Predicate Calculus Learning Outcome Analysis Representation Coding Representation
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INTRODUCTION “The know-how to program a computer to mimic the thought processes of an expert through an appropriate representation scheme ” is called knowledge representation (KR) It involves knowledge of a shell or a programming language that will represent the expert knowledge
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INTRODUCTION A number of KR schemes shares 2 common characteristics : a. They contain facts that can be used in reasoning b. They can be programmed with existing computer languages
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INTRODUCTION There are generally 2 types of KR schemes: a. Analysis representation Support knowledge acquisition during scope establishment and initial knowledge gathering Most techniques are pictorial such as - semantic networks - decision trees -tables b. Coding representation The working code of the ES either in the form of - frames or - production rules
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INTRODUCTION Knowledge Representation Analysis Representation Coding Representation Inference Frames Production rules Semantic networks Decision tables Decision trees Selected KR Schemes Key Idea
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KNOWLEDGE REPRESENTATION Analysis Coding Semantic Networks Decision Tables Decision Trees
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SEMANTIC NETWORKS Semantic networks are the most general representation scheme. Represent a graphical representation of knowledge that show hierarchical relationships between objects. Made up of a network of nodes and arc. The nodes represent objects and the arc the relationships between objects. KR Scheme 1 Node Arc
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SEMANTIC NETWORKS Example: KR Scheme 1
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SEMANTIC NETWORKS Example: License Seal Examination Air rescue Emergency landing procedures Olesek Insignia Shirt sleeve Two Male Harding Person Apparel Uniform Black Cap has- a certifie s has- a in-a in-an has- an is-on is-a number- of has- a is-a race-is is-a wear s is-a is-an KR Scheme 1
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SEMANTIC NETWORKS Nodes represent the objects, concepts, or events in the world. Names of the arcs correspond to names of relations indicate which concepts or objects are linked by the relations. KR Scheme 1
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SEMANTIC NETWORKS The 2 common arcs used are: IS-A is used to show class relationship . HAS-A is used to identify characteristics or attributes of the object nodes other arcs are used for definitional purpose only KR Scheme 1
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DECISION TABLES Organized in a spreadsheet format , using columns and rows The table divided into two parts : A list of attributes is developed and for each
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  • Winter '14
  • STUDENT
  • Logic, KR Scheme, KR Schemes

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