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Chapter 13 Artificial Intelligence and Expert Systems

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Title: Chapter 13 Artificial Intelligence and Expert Systems


1
Chapter 13Artificial Intelligence andExpert
Systems
2
Learning Objectives
  • List the basic concepts of artificial
    intelligence
  • Give examples of how artificial intelligence
    technologies have been used in business and other
    fields
  • Explain expertise, the purpose of expert systems
    in business and other professional domains, and
    why expert systems are so helpful in solving
    unstructured problems
  • Articulate the challenges involved in garnering
    knowledge for the construction of knowledge bases
  • Explain the concept of knowledge engineering

3
Artificial Intelligencein Business
4
Artificial Intelligencein Business (Cont.)
  • Artificial Intelligence
  • Attempt to emulate the human mind in machines
  • Robotics
  • Robots used to replace human laborers
  • Artificial Vision
  • Allows robots that move in space sense obstacles
  • Used in machines for sorting and identification

5
Artificial Intelligencein Business (Cont.)
  • Natural Language Processing
  • Programs that recognize human commands
  • Expert Systems
  • Programs that simulate human expertise
  • Neural Networks
  • Programs built to solve problems while learning
    and refining their knowledge

6
Artificial Intelligencein Business (Cont.)
7
Artificial Intelligencein Business (Cont.)
  • Fuzzy Logic
  • Based on rules that have no discrete boundaries
  • More closely mimics human problem solving
  • Used in appliances, locomotives, managerial
    decision making

8
Artificial Intelligencein Business (Cont.)
9
Artificial Intelligencein Business (Cont.)
10
Artificial Intelligencein Business (Cont.)
  • Genetic Algorithms
  • Mathematical functions that use Darwinian
    principals to improve an application
  • Intelligent Agents
  • Automatically wade through massive amounts of
    data to select and deliver the most suitable
    information

11
Artificial Intelligencein Business (Cont.)
12
Contribution ofExpert Systems
  • Planning
  • Decision making
  • Monitoring
  • Diagnosis
  • Training

13
Contribution ofExpert Systems (Cont.)
  • Incidental learning
  • Replication of expertise
  • Timely response
  • Consistent solutions

14
Development ofExpert Systems
  • What is Expertise?
  • Skill and knowledge whose input into a process
    results in performance high above the norm
  • Components of Expert Systems
  • The interface or dialog
  • The knowledge base
  • The interface engine

15
Development ofExpert Systems (Cont.)
16
Construction of Expert Systems
  • IF-THEN Rules
  • Most popular method of knowledge representation
  • Also called production rules
  • Systems hold facts in the form of IF-THEN
    statements

17
Construction of Expert Systems (Cont.)
18
Construction of Expert Systems (Cont.)
  • Knowledge Engineering
  • Asking experts appropriate questions and
    translating into a knowledge base
  • Some ESs take years
  • Knowledge engineer programmer who specializes in
    developing ESs

19
Construction of Expert Systems (Cont.)
  • Expert System Shells
  • Expert System that has been emptied of its
    knowledge
  • Used to build new ES
  • Forward Chaining
  • Result-driven process
  • Backward Chaining
  • Goal-driven process

20
Construction of Expert Systems (Cont.)
21
Factors Justifying the Acquisition of Expert
Systems
22
Expert Systems in Action
  • Medical management
  • Telephone network maintenance
  • Credit evaluation
  • Tax planning
  • Detection of insider securities trading
  • Detection of common metals

23
Expert Systems in Action (Cont.)
  • Mineral exploration
  • Irrigation and pest management
  • Diagnosis and prediction of mechanical failure
  • Class selection for students

24
Limitations of Expert Systems
  • Three limitations of ESs
  • Can handle only narrow domains
  • Do not possess common sense
  • Have a limited ability to learn

25
Ethical and Societal IssuesToo Sophisticated
Technology
  • Increasing dependence on machine intelligence
    raises legal and ethical issues.
  • Who is legally responsible for advice provided by
    a program?
  • Is expert judgment needed to interpret program
    output?
  • Does machine expertise replace or complement the
    real thing?
  • How do we know if the experts behind expert
    systems are expert at all?

26
Ethical and Societal IssuesToo Sophisticated
Technology
  • Malfunctions of an ES can be caused by anyone
    involved in the development
  • Experts who contribute knowledge
  • Knowledge engineer who builds the system
  • Professional who uses the ES
  • The person who is affected by the decision

27
Summary
  • Artificial intelligence has some basic concepts
  • Artificial intelligence is used in business and
    other fields
  • Expert systems are helpful in solving
    unstructured problems
  • Knowledge gathering is important for knowledge
    bases
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