Artificial Intelligence and Expert Systems

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Artificial Intelligence and Expert Systems

An Overview of

Artificial Intelligence

Artificial Intelligence

in Perspective

Artificial intelligence (AI)

Computers with the ability to mimic or duplicate the functions of the
human brain

Artificial intelligence system

People, procedures, hardware, software, data, and knowledge
needed to develop computer systems and machines that
demonstrate characteristics of intelligence

Characteristics of

Intelligent Behavior

Learn from experience

Handle complex situations

Solve problems when important information is missing

Determine what is important

Characteristics of

Intelligent Behavior

React quickly and correctly to a new situation

Understand visual images

s and manipulate symbols

Be creative and imaginative

Use heuristics

Natural vs. Artificial Intelligence

Since the term
artificial intelligence

was defined in the 1950s,
experts have disagreed about the difference between natural
and artificial lif

A driving force behind AI research is an attempt to understand
how humans actually reason and think.

Major Branches of

Artificial Intelligence

Expert systems


Vision systems

Natural language processing

Learning systems

ral network

Major Branches of

Artificial Intelligence

Expert systems

Hardware and software that stores knowledge and makes inferences,
similar to a human expert


Mechanical or computer devices that perform tasks requir
ing a high
degree of precision or repetitive hazardous tasks

Major Branches of

Artificial Intelligence

Vision systems

Hardware and software that permit computers to capture, store, and
manipulate visual images and pictures almost as precisely as hum

Natural language processing

Hardware and software that allow computers to understand and react
to statements and commands made in a human (natural) language

Major Branches of

Artificial Intelligence

Learning systems

A combination of software and hardware that allows the computer to
change how it functions or reacts to situations based on feedback it

Neural network

A computer system that can act like or simulate the functioning of a
human brain

An Overv
iew of

Expert Systems

Characteristics of

Expert Systems

Explain their reasoning or suggested decisions

Display “intelligent” behavior

Draw conclusions from complex relationships

Provide portable knowledge

Deal with uncertainty

Limiting Characteristics of Expert Systems

Not widely used or tested

Difficult to use

Limited to relatively narrow problems

Cannot readily deal with “mixed” knowledge

Possibility of error

Limiting Characteristics of Expert Systems

Cannot refine own knowledge base

Difficult to maintain

May have high development costs

Raise legal and ethical concerns

Capabilities of Expert Systems

Strategic goal setting




Quality control and mon


Factors that May Merit Use

of an Expert System

Provide a high potential payoff or significantly reduced
downside risk

Capture and preserve irreplaceable human expertise

Provide expertise needed at a number of locations at the same
time or in a hostile environment that is dangerous to human

Factors that May Merit Use

of an Expert System

Provide expertise that is expensive or rare

Develop a solution faster tha
n human experts can

Provide expertise needed for training and development to share
the wisdom of human experts with a large number of people

Components of

Expert Systems

The Knowledge Base

Stores all relevant information, data, rules, cases, and

then statements

Rules that suggest certain conclusions

Purpose: To hold relevant facts and information for the expert

The Knowledge Base

Assembling human experts

One of the challenges in developing a knowledge base

Use of fuzzy logic

A specialty research area in computer science that allows shades of
gray, or “fuzzy sets”

The Knowledge Base

Use of rules

A conditional statement that links given conditions to actions or

Use of cases

Involves finding cases stored in the knowledge base that are similar
to the problem or situation at hand and modifying the solutions to the
cases to fit the current problem or situation

The Inference Engine

Seeks information and relationships from the k
nowledge base
and provides answers, predictions, and suggestions

Backward chaining

Starts with conclusions and works backward to the supporting facts

The Inference Engine

Forward chaining

Starts with the facts and works to a conclusion

Reaches conclusions and yields more information with fewer queries
to the user than backward chaining, but requires more processing
and a greater degree of sophistication

The Explanation Facility

Allows users to understand how the system arrived at cert

The Knowledge

Acquisition Facility

Provides a convenient, efficient means for capturing and storing all
components of the knowledge base

[Figure 11.9]

The User Interface

Software employed for designing, creating, updating, and using
expert systems

Purpose: To make development and use of an expert system
easier for users and decision makers

Expert Systems Development

The Development Process

Participants in Developing

and Using Expert Systems

Participants in Developing

and Using Expert Systems


An area of knowledge

Domain expert

The individual or group who has the expertise or knowledge one is
trying to capture in the expert system

Participants in Developing

and Using Expert Systems

Knowledge engineer

An individual who has training and/or expertise in the design,
implementation, and maintenance of an expert system

Knowledge user

The individual or group who uses and bene
fits from the expert system

Expert Systems Development Tools and

Expert systems shells and products

A collection of software packages and tools used to design, develop, implement,
and maintain expert systems

Advantages of Expert Systems Shells and

Easy to develop and modify

Use of satisficing

Use of heuristics

Development by knowledge engineers and users

Expert Systems

Development Alternatives

house development from scratch

use development from a shell

shelf purchase: use of existing packages

Applications of Expert Systems and Artificial

Applications of ES and AI

Information management and retrieval

Embedded in products

Plant layout

Hospitals and medical facilities

Help desks and assistance

Employee performance evaluation

Loan analysis

Applications of ES and AI

Virus detection

Repair and maintenance



Integration with other systems in an organi
zation through a
common database

Information Systems Principles

The overall purpose of artificial intelligence applications in
business is to help the organization achieve its goals.

The ability to create machines that can reason will be possible
y once we truly understand our own processing for doing so.

Information Systems Principles

Sophisticated expert systems can be difficult, expensive, and
consuming to develop. Make sure that the potential
benefits are worth the effort and that various expert system
characteristics are balanced in terms of cost, control, and

mation Systems Principles

When human experts disagree on important points, it can be
difficult for expert system developers to determine which rules
and relationships to place in the knowledge base.

Information Systems Principles

Specifying the requi
rements for an expert system begins with
identifying the system's objectives and its potential use.

End of Chapter 11