Author: Grigoris Tziallas
Title: An Analysis and Design Methodology for Computer Aided Knowledge Engineering
Definition of a modeling formalism
and design methodology
for knowledge based systems
and the development
of a prototype tool
About the book
The transition of knowledge-based systems from the research laboratory to real operating environments requires the application of knowledge acquisition and specification methods. While numerous methods and techniques exist for knowledge acquisition, there is a lack of methods that specify goals, constraints and requirements of knowledge based-systems.
The main motivation of this work was to apply software engineering techniques and methodologies for the specification, analysis and design of knowledge-based systems.
An analysis and design methodology for knowledge-based systems is presented. The methodology uses a top down analysis and design method, which starts from a high-level abstract representation of a knowledge-based system, and through further refinement of specifications at lower abstraction and decomposition levels, ends up in a complete description of the application under development. The coupling of abstraction levels has been based mainly on Aristotle syllogism and Aristotle’s logic while the coupling of decomposition levels has been based on the coupling of form to material and used techniques of deep reasoning and qualitative physics.
The book describes the philosophical background, the analysis and design methodology, examples of use and a CASE tool for Computer Aided Knowledge Engineering.
A case study is also presented describing the development of a tutoring system for the maintenance and fault repairing of electric motors using the developed methodology and CASE tool.
Table of Contents
1.1 Introduction 111.2 Objectives of the thesis 121.3 Technical approach 121.4 Thesis overview 13
The specification stream 13The implementation stream 14The case study 14
1.5 Thesis organisation 15
APPROACH TO COMPUTER AIDED KNOWLEDGE ENGINEERING
2.1 Software engineering 172.2 CASE tools 182.3 AI techniques application to CASE tools. 182.4 Characteristics of AI computations 192.5 CASE techniques application to knowledge-based systems. 202.6 Approach to Computer Aided Knowledge Engineering 20
THE KNOWLEDGE REPRESENTATION PLATFORM
3.1 Philosophical background 233.1.1 Ontology and Metaphysics 233.1.2 Categories 243.1.3 Causality and Change 243.1.4 Knowledge and Logic 253.1.5 Teleology 263.2 AI paradigms 263.2.1 The Rule Paradigm 263.2.2 The object paradigm 263.2.3 The frame paradigm 273.2.4 Semantic Networks 273.2.5 Logic Programming 273.2.6 Multiparadigms 273.2.7 AI related issues 273.3 The developed modelling formalism 283.3.1 Schematic description of the modelling formalism 283.3.2 The specification language 313.3.3 Specification of objects 323.3.4 The semantics of causes 34
THE ANALYSIS AND DESIGN METHOD
4.1 Description of the analysis methodology 374.2 Coupling of decomposition levels 394.3 Coupling of abstraction levels 414.4 Design methodology 414.5 Specifications repository and executable specifications 434.6 Verification and validation 44
THE REASONING MECHANISMS
5.1 Overview 455.2 Causal reasoning 455.3 Deep reasoning 465.4 Syllogistic reasoning 475.5 Testing 475.6 Prototyping 48
THE ORGANON TOOL
6.1 Description of the Organon tool 516.1.1 The capture tools 526.1.2 The analysis tools 556.2 Using the Organon tool 566.2.1 Developing applications using Organon 566.2.2 The Organon functions 576.3 The Organon Implementation 626.3.1 Overview of the Organon Classes 62
DESCRIPTION OF THE CASE STUDY
7.1 The selected problem domain 657.2 Description of the tutoring system 657.3 Approach to high level parallelism 697.3.1 Description of a problem solver 707.3.2 Problem Description 717.3.3 Mapping of specifications on to the Model of Interactive Problem Solvers 727.4 Extensions to the Organon tool 73
THE TUTORING SYSTEM
8.1 The Tutoring system development process 758.1.1 The analysis and design phase 758.1.2 The model of interactive problem solvers 828.1.3 Implementation phase 828.2 Example of tutoring system operation and use 91
Appendix A 97
Appendix B 111
CLASSIFICATION OF DC MOTOR FAULTS 111CLASSIFICATION OF DC MOTOR SYMPTOMS 113CLASSIFICATION OF REPAIR TASKS 114CLASSIFICATION OF INSPECTION TASKS 115
Appendix C 117
TUTORING SYSTEM SURFACE BEHAVIOR 117