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Yetunde Folajimi
Teaching

Expert System

This course introduces the student to the general overview of expert systems, and how to build an expert system in a variety of application areas.
COURSE OUTLINE

INTRODUCTION TO KNOWLEDGE ENGINEERING
  • Introduction
  • Data, Information and knowledge
  • Engineering, software engineering & knowledge engineering
  • The role of knowledge engineer
  • Categories of KBS

INTRODUCTION TO EXPERT SYSTEM
  • What is an ES?
  • Conventional and ES
  • The Characteristic of ES
  • The Structure of ES
  • The Characteristic of ES
  • ES Development Life Cycles
  • Participants in ES Development
  • Selected Business Expert Systems and Functions
  • Advantages of ES
  • Limitations of ES
  • When to Use Expert Systems
  • Justifying the Problem Domain
  • MYCIN: A medical expert system
  • WEBCANDI: A Web based Expert System for Cancer Diagnosis 
  • Building Tools

KNOWLEDGE ACQUSITION 
  • Introduction
  • Scopes of knowledge
  • Knowledge Acquisition
  • Problems in Knowledge Acquisition
  • Knowledge Acquisition Techniques
  • Structuring Knowledge Graphically

THE REPRESENTATION OF KNOWLEDGE
  • Introduction
  • Semantic Networks
  • Decision Tables
  • Decision Trees
  • Frames
  • Production Rules
  • Logic
  • Propositional Logic 
  • Predicate Calculus


INFERENCING STRATEGIES
  • Introduction
  • Categories of Reasoning
  • Inference Techniques 
  • Control Strategies
  • Comparative Summary of Backward and Forward Chaining
  • Conflict Resolution
  • Goal Agenda

REASONING UNDER UNCERTAINTY
  • Certainty Theory
  • Fuzzy approach
  • Bayesian approach

Lecture Slides

1-expertsyoverview.pdf
File Size: 669 kb
File Type: pdf
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Module 2-knowledge engineering
File Size: 4073 kb
File Type: pdf
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Module 3-introduction to ES
File Size: 15906 kb
File Type: pdf
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4-knowledgeacquisition.pdf
File Size: 11755 kb
File Type: pdf
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Module 5: Representation of Konwoledge
File Size: 12050 kb
File Type: pdf
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Module 6- inferencing
File Size: 2668 kb
File Type: pdf
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Module 7: Reasoning Under uncertainty: Certainty approach
File Size: 2195 kb
File Type: pdf
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Module 8: Reasoning under uncertainty: Fuzzy approach
File Size: 3221 kb
File Type: pdf
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Module 9: Reasoning under uncertainty: Bayesian approach
File Size: 1404 kb
File Type: pdf
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Additional readings:

Expert System: an Introduction