Business Expert Systems Expert Systems An intelligent computer

Business. Expert Systems

Expert Systems “. . An intelligent computer program that uses knowledge and inference procedures to solve problems that are difficult enough to require significant human expertise for their solution. . ” (Feigenbaum 1982)

Expert System Basic concept of expert system : � User supplies facts or other information to the expert system and receives expert advice or expertise in response. Internally, the expert system consists of two main components : � the knowledge-base contains the knowledge � the inference engine draws conclusions from the knowledge Expert System User Facts Expertise Inference Engine Knowledge-base

Expert System Functionality • Assist human expert when integrating various decisions • Replace human expert decision making when not available Expert systems : programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms)

Applications of Expert Systems Peachtree: Used by accountant for making Database, Financial documents

Applications of Expert Systems PUFF: Medical system for diagnosis of respiratory conditions PROSPECTOR: Used by geologists to identify sites for drilling or mining

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.

Why use Expert Systems? • Experts are not always available. An expert system can be used anywhere, any time. • Human experts are not 100% reliable or consistent • Experts may not be good at explaining decisions • Cost effective

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

Limitations of Expert Systems • Limited to relatively narrow problems • Cannot readily deal with “mixed” knowledge • Possibility of error • Cannot refine own knowledge base • Difficult to maintain • May have high development costs • Raise legal and ethical concerns