CSC 554: Knowledge-Based Systems Part-1 By Dr. Syed Noman Hasany Assistant 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

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 Inference Engine Knowledge Base Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson 6th 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?