Expert systems (ES) are one of the prominent research domains of AI. It is introduced by the researchers at Stanford University, Computer Science Department.
The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise.
Characteristics of Expert Systems
• High performance
• Highly responsive
Capabilities of Expert Systems
The expert systems are capable of −
• Instructing and assisting human in decision making
• Deriving a solution
• Interpreting input
• Predicting results
• Justifying the conclusion
• Suggesting alternative options to a problem
They are incapable of −
• Substituting human decision makers
• Possessing human capabilities
• Producing accurate output for inadequate knowledge base
• Refining their own knowledge
Components of Expert Systems
The components of ES include −
• Knowledge Base
• Interface Engine
• User Interface
It contains domain-specific and high-quality knowledge. Knowledge is required to exhibit intelligence. The success of any ES majorly depends upon the collection of highly accurate and precise knowledge.
What is Knowledge
The data is collection of facts. The information is organized as data and facts about the task domain. Data, information, and past experience combined together are termed as knowledge.
Components of Knowledge Base
The knowledge base of an ES is a store of both, factual and heuristic knowledge.
• Factual Knowledge − It is the information widely accepted by the Knowledge Engineers and scholars in the task domain.
• Heuristic Knowledge − It is about practice, accurate judgement, one’s ability of evaluation, and guessing.
It is the method used to organize and formalize the knowledge in the knowledge base. It is in the form of IT-THEN-ELSE rules.
The success of any expert system majorly depends on the quality, completeness, and accuracy of the information stored in the knowledge base.
The knowledge base is formed by readings from various experts, scholars, and the Knowledge Engineers. The knowledge engineer is a person with the qualities of empathy, quick learning, and case analyzing skills.
He acquires information from subject expert by recording, interviewing, and observing him at work, etc. He then categorizes and organizes the information in a meaningful way, in the form of IF-THEN-ELSE rules, to be used by interference machine. The knowledge engineer also monitors the development of the ES.
Use of efficient procedures and rules by the Interface Engine is essential in deducting a correct, flawless solution.
In case of knowledge-based ES, the Interface Engine acquires and manipulates the knowledge from the knowledge base to arrive at a particular solution.