This slide is about Expert System under Artificial Intelligence.

1. EXPERT SYSTEMS

2. Introduction
• A computer system that uses AI technologies to simulates the
decision-making process of a human expert in a particular field.
• It is an “intelligent” program that solves problems in a narrow
problem area by using high-quality, specific knowledge rather
than a algorithm.

3. Block Diagram of an Expert System

4. 1. Knowledge Base
• The component of an expert system that contains the
system’s knowledge is called its knowledge base.
• It is critical to the way most expert systems are constructed.
• Contains both declarative and procedural knowledge.
• Rule-based production system approach is used.
Major Components of Expert System

5. 2. Inference Engine
• An inference engine tries to derive answers from a
knowledge base.
• It is the brain of the expert systems that provides a
methodology for reasoning about the information in the
knowledge base, and for formulating conclusions.
• In effect, an inference engine “runs” an expert system.

6. 3. User Interface
• It enables the user to communicate with an expert system.
• Communication is bidirectional.
Besides these three components, there is a Working Memory - a
data structure which stores information about a specific run. It
holds current facts and knowledge.

7. Examples of Expert Systems
• PXDES
• CaDet
• DXplain
• MYCIN

8. Stages of Expert System Development
• An expert system typically is developed and refined over a
period of several years.
• There are 5 distinct stages of expert system development.
Identification ImplementationFormalizationConceptualization Testing
Fig: Different Phases of Expert
System Development

9. Features of an Expert Systems
• Useful
• Usable
• Educational when appropriate
• Explain its advice
• Respond to simple questions
• Learn new Knowledge
• Easily Modified

10. Limitations
• Limitations of the technology
• Difficult knowledge acquisition
• Difficult to maintain
• High development costs

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