Specialized Business
Information Systems
Chapter 7
Fundamentals of Information
Systems, Second Edition
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The Nature of Intelligence
• Learn from experience & apply the knowledge
– Deep Blue improves its performance by playing with
humans
• Handle complex situations
– Traffic problem in Istanbul
• Solve problems when important information is
missing
– Based on available information
• Determine what is important
– Choose which facts to use to compute the solution
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The Nature of Intelligence
• React quickly and correctly to new situations
– Requires understanding the new situation
• Understand visual images
– Requires perception
• Process and manipulate symbols
– Computers are better at dealing with numbers
• Be creative and imaginative
• Use heuristics
– Rules of thumb from experience
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A comparison of Natural and Artificial
Intelligence
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A Conceptual Model of Artificial
Intelligence
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What is an Expert System?
• Hardware and software that contain knowledge and
manipulate knowledge by inferences
• Mycin (Shortliffe 1976): Expert system for medicine
– Program for advising physicians on treating
bacterial infections
– Question and answer dialogues with user
– Accounts for uncertainties
– Explains its reasoning
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Characteristics of an Expert System
• Can explain their reasoning or suggested decisions
– Why recommend a certain medicine?
• Can display “intelligent” behavior
• Can draw conclusions from complex relationships
– A patient is diagnosed with two diseases,
– The cures for the diseases may have conflicts
• Can provide portable knowledge
– Capture knowledge in one’s brain
• Can deal with uncertainty
– A patient is diagnose without running all the tests
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Characteristics of an Expert System
• Not widely used or tested
• Limited to relatively narrow problems
• Cannot readily deal with “mixed” knowledge
– Expert systems should talk to each other
• Cannot refine its own knowledge
– Should be able to keep a consistent knowledgebase
– Should have a way to gain new knowledge
• May have high development costs
• Raise legal and ethical concerns
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When to Use Expert Systems
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High payoff
Preserve scarce expertise
Provide more consistency than humans
Faster solutions than humans
Training expertise
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Components of an Expert System
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The Relationships Among Data,
Information, and Knowledge
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Rules for a Credit Application
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The Knowledge Acquisition Facility
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Knowledge Base
• Assembling human experts
– Combine knowledge from several experts
– Disagree on many items
• The use of fuzzy logic
– For relations that are not precise
– Is a 50-year old man old?
– Help computers deal with imprecise
knowledge
– Ex: Washing machines; Auto-focus cameras
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Knowledge Base
• The use of rules
– Rule: Conditional statement (if … then)
– If the condition matches, the action fires
– More rules generally mean more precision
• The use of cases
– Template of problems or situations
– To find the solution of a new case, find similar
old cases and apply result
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Inference Engine (1)
• Use information and relations to derive new facts
to solve problems or predict possible outcomes
• Main reasoning component
• Find the right facts, apply the right relations, etc.
• Ex: Facts: male(Ali), female(Oya)
• Relations: father(X, Y) => male(X)
• The engine can conclude that Oya cannot be a
father.
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Inference Engine (2)
• Backward chaining
– You start with conclusions
– You want to find out if you can get to the conclusion
from your facts
• Forward chaining
– You start with facts and try to reach conclusions
– More expensive since it can generate many
conclusions
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Other Components
• Explanation Facility
– Enables the expert system to explain its reasoning
– Helps the user to judge the expert system
• Knowledge Acquisition Facility
– Get and update knowledge
– Provide a way to capture and store knowledge
– Can be semi-automated
• User Interface
– Help users interact with the system
– Improve usability
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Expert Systems Development
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Participants in Developing and Using
Expert Systems
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Domain Expert
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Recognize the real problem
Develop a general framework for problem solving
Formulate theories about the situation
Develop and use general rules to solve a problem
Know when to break the rules or general principles
Solve problems quickly and efficiently
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Other participants
• Knowledge Engineer
– Works in design and implementation of the expert
system
– Has considerable information about expert systems
• Knowledge User
– End user who will benefit from the system
– No need to know anything about expert systems
– Can help in testing
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Expert Systems Development
Alternatives
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Applications of Expert System and
Artificial Intelligence
• Credit granting and loan analysis
• Stock Picking
• Catching cheats and terrorists
– NORA (Non-obvious Relationship Awareness)
• Budgeting
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Applications of Expert System and
Artificial Intelligence
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Games: Proverb solves crossword puzzles
Writing: Evaluate and rate writings
Information management and retrieval
Virus detection
– Learns the actions of a virus
• Hospitals and medical facilities
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Virtual Reality
Enables one or more users to move and react in a
computer-simulated environment
• Immersive virtual reality - user becomes fully
immersed in an artificial, three-dimensional world that is
completely generated by a computer
• Virtual reality system - enables one or more users to
move and react in a computer-simulated environment
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Interface Devices
• Head mounted display (HMD)
• Binocular Omni-Orientation Monitor (BOOM)
• CAVE
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The BOOM, a Head-Coupled Display
Device
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Viewing the Detroit Midfield Terminal in an Immersive
CAVE System
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Useful Applications
• Medicine – used to link stroke patients to
physical therapists
• Education and training – used by military for
aircraft maintenance
• Entertainment
– Star Wars Episode II: Attack of the Clones
• Real Estate Marketing and Tourism
– Used to increase real estate sales
– Virtual reality tour of the White House
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Segway
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Robotics
• Mechanical or computer devices that can
move autonomously
• Manufacturers use robots to assemble or
paint products
• Asimo in Istanbul: Shake hands, dance
• Unmanned Combat Air Vehicles (UCAVs):
Identify and destroy targets without human
intervention
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Vision Systems
• Capture, store, manipulate visual images
• Fingerprint analysis: Store a database of
fingerprints and information about the
owners.
• Match a fingerprint with an existing entry in
the database
• Mostly recognize black and white
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Natural Language Processing
• Understand and react to statements in
natural language
• Three levels of understanding
– Commands
– Discrete
– Continuous
• Talk to a computer; computer converts
languages to commands understandable
by computers
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Learning Systems
• Change its behavior over time
– Computer takes an action
– User gives feedback
– Based on the feedback, computer modifies its
action
• First train the system; then try on test data
• Amazon.com learns user models as users
browse and buy goods
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Summary
• Artificial intelligence - used to describe computers with ability to
mimic or duplicate functions of the human brain
• Intelligent behavior - includes the ability to learn from experience
• Expert systems - can explain their reasoning (or suggested
decisions) and display intelligent behavior
• Virtual reality system - enables one or more users to move and
react in a computer-simulated environment
• Special-purpose systems - assist organizations and individuals in
new and exciting ways
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Principles and Learning Objectives
• Artificial intelligence systems form a broad and diverse set of
systems that can replicate human decision making for certain
types of well-defined problems.
– Define the term artificial intelligence and state the objective of
developing artificial intelligence systems.
– List the characteristics of intelligent behavior and compare the
performance of natural and artificial intelligence systems for each of
these characteristics.
– Identify the major components of the artificial intelligence field and
provide one example of each type of system.
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Principles and Learning Objectives
• Expert systems can enable a novice to perform
at the level of an expert but must be developed
and maintained very carefully.
– List the characteristics and basic components of
expert systems.
– Outline and briefly explain the steps for developing an
expert system.
– Identify the benefits associated with the use of expert
systems.
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Principles and Learning Objectives
• Virtual reality systems have the potential to reshape the
interface between people and information technology by
offering new ways to communicate information creatively.
– Define the term virtual reality and provide three examples of
virtual reality applications.
• Special-purpose systems can help organizations and
individuals achieve their goals.
– Discuss examples of special-purpose systems for organizational
and individual use.
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