## 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.

## Readings:

The adopted textbook for this course is Expert Systems, Principles and Programming, 4th Edition by by Joseph C. Giarratano and Gary D. Riley

Watch out for additional reading materials

Watch out for additional reading materials

**COURSE OUTLINE**

**INTRODUCTION**

- Meaning of an expert system
- understanding the problem domain and knowledge domain
- advantages of an expert system
- stages in ES development
- general characteristics of an expert system
- Examples of earlier expert systems
- applications of expert systems in use today
- structure of a rule-based expert system
- procedural and nonprocedural paradigms
- characteristics of artificial neural systems

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Expert System Slide 1 - Introduction

**THE REPRESENTATION OF KNOWLEDGE**

- introduction to logic
- formal logic and informal logic
- knowledge representation
- Introduction to semantic nets
- Introduction to frames
- logic and set symbols
- propositional and first order predicate logic
- quantifiers

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**INFERENCE**

- Definitions of trees, lattices, and graphs
- state and problem spaces
- AND-OR trees and goals
- methods and rules of inference
- characteristics of first-order predicate logic and logic systems
- shallow and causal reasoning
- resolution in first-order predicate logic
- forward and backward chaining
- Metaknowledge
- Markov decision process

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**REASONING UNDER UNCERTAINTY**

- Meaning and theories of uncertainty
- Errors of uncertainty and induction
- classical probability, experimental, and subjective probability, and conditional probability
- hypothetical reasoning and backward induction.
- temporal reasoning and Markov chains
- odds of belief, sufficiency, and necessity
- role of inference nets in expert systems

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**INEXACT REASONING**

- sources of uncertainty in rules
- methods for dealing with uncertainty
- the theory of uncertainty based on fuzzy logic
- commercial applications of fuzzy logic

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**EXPERT SYSTEMS DESIGN**

- ES problem selection
- Stages in the development of an expert system
- the role of the knowledge engineer in the building of an expert system
- expert systems life cycles and models

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**INTRODUCTION TO CLIPS**

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**Homework**

1. Go thrrough existing literature concerning any two (2) from each group and discuss their performance, problems, design and implementation issues:

Chemistry ES: MOLGEN, SPEX, SECS

MEDICAL ES: PUFF, ABEL, MYCIN, ONOCIN, GUIDON

Electronic ES: ACE, PALLADIO, SOPHIE

Geology ES: PROSPECTOR, DIPMETER, MUD

Computer ES: BDS, XCON, YES/NO

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**PAST QUESTIONS**

C/A test 2013/2014 session