CSC 554: Knowledge-Based Systems

Part-1 By

Dr. Syed Noman HasanyAssistant Professor, CoC

Qassim University

CSC 554: Knowledge-Based Systems• 3 credit hrs.• Contents

– Expert systems – Presentation of knowledge representation paradigms– Rule-based systems – Inference rules – Resolution – Reasoning under uncertainty – Developing a knowledge-based system prototype, from knowledge

acquisition (including mock interviews with a domain expert) – Knowledge modelling, design, implementation and testing – Prototype system development using tools such as Eclipse or CLIPS (Fuzzy

CLIPS).• Textbook

– Ullman J. D., “Principles of Database and Knowledge-Base Systems Volume II: The New Technologies”.

Part-1

Expert Systems

Expert Systems• An expert system is a computer program

that is designed to hold the accumulated knowledge of one or more domain experts in order to imitate expert reasoning processes and knowledge in solving specific problems.

Definition

• Involves– Categorization– characterization

Why use Expert Systems?

• Experts are not always available. An expert system can be used anywhere, any time.

• Decreased decision making time• Human experts are not 100% reliable or

consistent• Experts may not be good at explaining

decisions• Cost effective (for the user)

7

Three Major ES Components

User Interface

InferenceEngine

KnowledgeBase

Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson6th ed, Copyright 2001, Prentice Hall, Upper Saddle River, NJ

Components of an Expert System• The knowledge base is the collection of facts

and rules which describe all the knowledge about the problem domain.

• The inference engine is the part of the system that chooses which facts and rules to apply when trying to solve the user’s query.

• The user interface is the part of the system which takes in the user’s query in a readable form and passes it to the inference engine. It then displays the results to the user.

User Interface

• Language processor for friendly, problem-oriented communication

• NLP, or menus and graphics

Knowledge Base

• The knowledge base contains the knowledge necessary for understanding, formulating, and solving problems

Inference Engine

• The brain of the ES • The control structure (rule

interpreter)• Provides methodology for

reasoning

Some Applications of Expert Systems

PROSPECTOR:Used by geologists to

identify sites for drilling or mining

PUFF:Medical system

for diagnosis of respiratory conditions

Some Applications of Expert Systems

DESIGN ADVISOR:Gives advice to designers of

processor chips

MYCIN:Medical system for diagnosing blood

disorders. First used in 1979

Problems with Expert Systems

• Limited domain• Systems are not always up

to date, and don’t learn• No “common sense”• Experts needed to setup

and maintain system

Legal and Ethical Issues

• Who is responsible if the advice is wrong?– The user?– The domain expert?– The knowledge engineer?– The programmer of the expert system shell?– The company selling the software?