1. What is an Expert System?
 An Expert System is a computer system
that emulates the decision-making
ability of a human expert.
 Expert systems are designed to solve
complex problems by reasoning about
knowledge, like an expert.

2. CONT…
 Expert systems are:
 Knowledge based systems
 Part of the Artificial Intelligence field
 Computer programs that contain some
subject-specific knowledge of one or more
human experts
 Systems that utilize reasoning capabilities
and draw conclusions.

3. 4 Major Components
Every expert system consists of four principal
parts
 The rule base or knowledge base
 Working storage
 The inference engine
 User interface

4. 1) The rule base or knowledge base
 The knowledge base is the collection of
facts and rules which describe all the
knowledge about the problem domain
 Contain everything necessary for
understanding, formulating and solving a
problem.
 Stores all relevant
information, data, rules, cases, and
relationships used by the expert system

5. 2) WORKING MEMORY (SHORT
TERM MEMORY)
Contains facts about a problem that are
discovered during consultation with the expert
system.
 System matches this information with
knowledge contained in the knowledge base to
infer new facts.
 The conclusion reach will enter the working
memory.


6. 3) The inference engine
The inference engine is the part of the system
that chooses which facts and rules to apply when
trying to solve the user’s query.
 It taps the knowledge base and working memory
to derive new information and solve problems
 The inference engine is a computer program
designed to produce reasoning on rules
 It is based on logic

7. 4) THE USER INTERFACE
The user interface is the part of the system which takes
in the user’s query in a readable form and passes it to
the inference engine. It then displays the results to the
user.
 The user communicates with the expert system
through the user interface.
 It allows the user to query the system, supply
information and receive advice.
 The aims are to provide the same form of
communication facilities provided by the expert.
 The code that controls the dialog between the user and
the system

8. Graphical View
Knowledge Base
Domain Knowledge
Inference Engine
Working Memory
Case/Inferred Facts
Conclusion
User
Case Facts
Conclusion

9. Types of Expert Systems
 Rule-based Systems
 Knowledge represented by series of rules
 Frame-based Systems
 Knowledge represented by frames
 Hybrid Systems
 Several approaches are combined, usually rules and frames
 Model-based Systems
 Models simulate structure and functions of systems
 Off-the-shelf Systems
 Ready made packages for general use
 Custom-made Systems
 Meet specific need

10. Comparison
Issues
Human Expert
Expert System
Availability
Limited
Always
Geographic
location
Locally available
Anywhere
Durability
Depends on
individual
Non-perishable
Performance
Variable
High
Speed
Variable
High
Cost
High
Low
Learning Ability
Variable/High
Low
Explanation
Variable
Exact

11. Advantages
 Quick availability
 Reduce employee training costs
 Reduce the time needed to solve problems.
 Combine multiple human expert intelligences
 Reduce the amount of human errors.
 Never "forgets" to ask a question,
 Ability to solve complex problems
 Consistent answers for repetitive decisions, processes and
tasks
 Excellent Performance
 Provide Explanation
 Fast response