Architecture of An Expert System

Architecture of an Expert System

The architecture of a typical expert system is shown in the figure given below.

As shown in the figure above there are major components that need to be described as follows:

1. Knowledge Base:- The knowledge base contains facts and rules above some specialized knowledge domain.
2. Inference Engine:- The inference engine accepts input queries and respond to the questions through the interface and use this dynamic information together with static knowledge stored in the knowledge base. The knowledge base is used to derive the conclusion about the current situation that is presented to the user. The inferring of the process is carried out recursively in three stages. They are:
   Match.
   Select.
   Execute.
   
   During the match state, the contents of working memory are compared to the facts and rules that are stored in the knowledge base. After matching the criteria for selection may be the most recent use rule condition specificity. The selected rule is then executed and action part of the rule is then carried out.
   
   
3. Interface:- The interface permits the user to communicate with the user.
   
   
4. Explanation Facility:-The explanation module provides the user with an explanation of the reasoning process. In order to respond the query, the explanatory module traces the chain of rules. The sequence of the rule that leads to the conclusion is then printed for the user in an easy way. This permits the user to actually see the reasoning process followed by the system in arriving at the conclusion. If the user does not agree with the reasoning steps presented then they may be changed using the help of an editor.
   
   
5. Knowledge Engineer:-A knowledge engineer is someone who is capable of designing the buildings and testing the expert system. The knowledge engineer introduces the domain expert to find out how a particular problem is solved. Knowledge engineer establishes the reasoning method which is used to handle the facts and rules in the expert system. He is also responsible for testing, revising and integrating the expert system into the workplace.

References:

1. Elaine Rich, Kevin Knight 1991, "Artificial Intelligence".
2. Nilsson, Nils J. Principles of Artificial Intelligence, Narosa Publishing House New Delhi, 1998.
3. Norvig, Peter & Russel, Stuart Artificial Intelligence: A modern Approach, Prentice Hall, NJ, 1995
4. Patterson, Dan W. Introduction to Artificial Intelligence and Expert Systems, Prentice Hall of India Private Limited New Delhi, 1998.