Artificial Intelligence - Expert Systems

Expert systems

The expert system is a major application of AI today. Also known as knowledge-based systems, expert systems act as intelligent assistants to human experts or serve as a resource to people who may not have access to an expert. The major difference between an expert system and a simple database containing information on a particular subject is that the database can only give the user discrete facts about the subject, whereas an expert system uses reasoning to draw conclusions from stored information. The purpose of this AI application is not to replace our human experts, but to make their knowledge and experience more widely available.

An expert system has three parts: knowledge base, inference engine, and user interface. The knowledge base contains both declarative (factual) and procedural (rules-of-usage) knowledge in a very narrow field. The inference engine runs the system by determining which procedural knowledge to access in order to obtain the appropriate declarative knowledge, then draws conclusions and decides when an applicable solution is found.

An interface is usually defined as the point where the machine and the human "touch." An interface is usually a keyboard, mouse, or similar devices. In an expert system, there are actually two different user interfaces: One is for the designer of the system (who is generally experienced with computers) the other is for the user (generally a computer novice). Because most users of an expert system will not be computer experts, it is important that system be easy for them to use. All user interfaces are bi-directional; that is, are able to receive information from the user and respond to the user with its recommendations. The designer's user interface must also be capable of adding new information to the knowledge base.