Expert Systems Lab Course

'1 Introduction.- 1.1 What Do We Mean by Expert System?.- 1.2 What Is Prolog?.- 1.3 Which Implementation of Prolog Are We Using?.- 1.4 How Is This Lab Structured?.- 2 Characteristics and Components of an Expert System.- 2.1 The Concept and Areas of Application.- 2.2 Human Versus Machine Knowledge.- 2.3 Knowledge Base and Knowledge Bank.- 2.4 Rule Knowledge.- 2.5 The Inference Engine.- 2.6 Instantiation of Variables.- 2.7 Applications Problems.- 2.8 Classification of Typical Expert Systems.- 3 A Model System for Transit Fare Information.- 3.1 The Problem.- 3.2 Transit Fare Rules.- 3.3 Conducting a Dialog.- 3.4 Control Structure and the Rule Interpreter.- 3.5 Gathering Case Data.- 3.6 The Inference Tree and Protocolling.- 3.7 Explanations.- 3.8 Equivalent Answers.- 3.9 Weaknesses and Possible Improvements.- 4 The Representation and Processing of Knowledge.- 4.1 System Architecture.- 4.2 System Development.- 4.3 Modularization.- 4.4 Knowledge Structures and Deductive Mechanisms.- 4.5 Production Systems.- 4.6 The Direction of Chaining.- 4.7 Inference Trees.- 4.8 Rule Modification and Non-monotonic Logic.- 4.9 Control of Flow.- 5 Dialog and Explanatory Components.- 5.1 Implicit Dialog Texts.- 5.2 The Structure and Processing of Rules.- 5.3 Facts and Degrees of Certainty.- 5.4 The Inference Engine.- 5.5 Gathering Case Data.- 5.6 Vague Knowledge.- 5.7 Instructing the User to Perform a Test.- 5.8 Explaining the Reason for a Question.- 5.9 Presenting and Explaining the Results.- 5.10 "Why Not" Explanations.- 5.11 Listing the Current Contents of the Fact Base.- 5.12 Shortcomings and Possible Improvements.- 6 "Experience" and "Learning".- 6.1 User Hunches.- 6.2 Diagnostic Phases.- 6.3 Heuristics.- 6.4 Diagnostic Statistics.- 6.5 Learning from Experience.- 6.6 Shortcomings and Possible Improvements.- 7 Object-Oriented Knowledge Management.- 7.1 Objects, Instances and Classes.- 7.2 Representing Objects with Frames.- 7.3 The Organization of an Object Base.- 7.4 Primitive