Unit 2
Executive Information and support systems
Business expert system -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
● Understandable
● Reliable
● Highly responsive
The expert systems are capable of −
● Advising
● Instructing and assisting human in decision making
● Demonstrating
● Deriving a solution
● Diagnosing
● Explaining
● 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
● Inference Engine
, ● User Interface
Let us see them one by one briefly −
Knowledge Base -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.
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.
Inference Engine -Use of efficient procedures and rules by the Inference Engine is essential in deducting a
correct, flawless solution. In case of knowledge-based ES, the Inference Engine acquires and manipulates the
knowledge from the knowledge base to arrive at a particular solution.
In case of rule based ES, it −
● Applies rules repeatedly to the facts, which are obtained from earlier rule application.
● Adds new knowledge into the knowledge base if required.
● Resolves rules conflict when multiple rules are applicable to a particular case.
User Interface User interface provides interaction between user of the ES and the ES itself. It is generally
Natural Language Processing so as to be used by the user who is well-versed in the task domain. The user of the
ES need not be necessarily an expert in Artificial Intelligence.
It explains how the ES has arrived at a particular recommendation. The explanation may appear in the
following forms −
● Natural language displayed on screen.
● Verbal narrations in natural language.
● Listing of rule numbers displayed on the screen.
The user interface makes it easy to trace the credibility of the deductions.
Expert Systems Limitations
Executive Information and support systems
Business expert system -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
● Understandable
● Reliable
● Highly responsive
The expert systems are capable of −
● Advising
● Instructing and assisting human in decision making
● Demonstrating
● Deriving a solution
● Diagnosing
● Explaining
● 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
● Inference Engine
, ● User Interface
Let us see them one by one briefly −
Knowledge Base -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.
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.
Inference Engine -Use of efficient procedures and rules by the Inference Engine is essential in deducting a
correct, flawless solution. In case of knowledge-based ES, the Inference Engine acquires and manipulates the
knowledge from the knowledge base to arrive at a particular solution.
In case of rule based ES, it −
● Applies rules repeatedly to the facts, which are obtained from earlier rule application.
● Adds new knowledge into the knowledge base if required.
● Resolves rules conflict when multiple rules are applicable to a particular case.
User Interface User interface provides interaction between user of the ES and the ES itself. It is generally
Natural Language Processing so as to be used by the user who is well-versed in the task domain. The user of the
ES need not be necessarily an expert in Artificial Intelligence.
It explains how the ES has arrived at a particular recommendation. The explanation may appear in the
following forms −
● Natural language displayed on screen.
● Verbal narrations in natural language.
● Listing of rule numbers displayed on the screen.
The user interface makes it easy to trace the credibility of the deductions.
Expert Systems Limitations
