These are the notes from an AI evening lecture course I gave at Hong Kong Productivity Council in 1987, so you should not be surprised to find it's a bit out of date now. In particular, the following topics are entirely absent:

• Neural Networks
• Common Sense Reasoning
• Agents
• Subsumption Architectures

The course comprised 20 hours of lectures, and so didn't go into too much depth.

TABLE OF CONTENTS

1. Introduction: Can a Machine Think?
2. Propositional and Predicate Logic
3. Alternative Logics: Modal Logic and Fuzzy Logic
4. Structured Knowledge Representation: Semantic Nets and Frame Systems
5. Augmented Transition Networks
6. Forward Chaining Production Systems
7. Backward Chaining Production Systems
8. Search Algorithms
9. Planning
10. Metaknowledge
11. Machine Learning, including:
    • Learning from Examples
    • Concept Learning
    • Learning by Analogy
    • Learning by Discovery
12. MYCIN: An Expert System for Medical Diagnosis
13. AM and Eurisko: A Case Study of Discovery Learning
14. Cognitive Science: How do People Think?
15. Applying AI Techniques
16. Bibliography

Copyright 1987 D. Fisk

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