Expert Systems

What is an Expert System? A system that uses human expertise to make complicated decisions. Simulates reasoning by applying knowledge and interfaces. Uses expert’s knowledge as rules and data within the system. Models the problem solving ability of a human expert.

Expert System An expert system is a system that employs human knowledge captured in a computer to solve problems that ordinarily require human expertise.(Turban) A computer program that emulates the behaviour of human experts who are solving real-world problems associated with a particular domain of knowledge. (Pigford & Braur)

Components of an Expert System Knowledge Base User User Interface Inference Engine

4 Components of an ES Knowledge Base Reasoning or Inference Engine User Interface Explanation Facility

Inference Engine Asks the user questions about what they are looking for. Applies the knowledge and the rules held in the knowledge base. Appropriately uses this information to arrive at a decision.

User Interface Allows the expert system and the user to communicate. Finds out what it is that the system needs to answer. Sends the user questions or answers and receives their response.

Expert System Structure Knowledge Based Rules Expert Interpreter Inference Engine Natural Language Interface Data base Context Set of facts User

Knowledge Base Represents all the data and information imputed by experts in the field. Stores the data as a set of rules that the system must follow to make decisions.

Knowledge Acquisition Expert System Knowledge Engineer Human Expert

Knowledge Acquisition Knowledge acquisition is the process by which knowledge available in the world is transformed and transferred into a representation that can be used by an expert system. World knowledge can come from many sources and be represented in many forms. Knowledge acquisition is a multifaceted problem that encompasses many of the technical problems of knowledge engineering, the enterprise of building knowledge base systems. (Gruber).

Knowledge Acquisition Five stages: Identification: - break problem into parts Conceptualisation: identify concepts Formalisation: representing knowledge Implementation: programming Testing: validity of knowledge

Early Expert Systems DENDRAL – used in chemical mass spectroscopy to identify chemical constituents MYCIN – medical diagnosis of illness DIPMETER – geological data analysis for oil PROSPECTOR – geological data analysis for minerals XCON/R1 – configuring computer systems

Advantages of Expert Systems Easy to develop and modify The use of satisficing The use of heuristics Development by knowledge engineers and users

Applications of Expert Systems and Artificial Intelligence Credit granting Information management and retrieval AI and expert systems embedded in products Plant layout Hospitals and medical facilities Help desks and assistance Employee performance evaluation Loan analysis Virus detection Repair and maintenance Shipping Marketing Warehouse optimization