Transcript CHAPTER

CHAPTER 5
DECISION SUPPORT AND
ARTIFICIAL INTELLIGENCE
Brainpower for Your
Business
5-2
Introduction
The Survival of Your Business
Depends on Effective Decision
Making
IT can supplement human decision
making
 IT can (sometimes) replace human
decision making

GAS SALE QUANTITY FORECAST
Smooth Constant a=0.3
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系列5
Hennery Expert System
5-3
Introduction
YOUR FOCUS IN THIS CHAPTER
Types of Decisions
 The Decision-Making Process
 IT Brainpower
 How IT Brainpower Supports the
Decision-Making Process

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Types of Decisions
TYPES OF DECISIONS YOU
FACE
STRUCTURED DECISIONS - those with a
set of steps that guarantee the correct
solution.
NONSTRUCTURED DECISIONS - those with
no rules or criteria that guarantee a good
solution.

STRUCTURED
DECISIONS
Expand
business to
West of China
NONSTRUCTURED
DECISIONS
SOMEWHERE IN
BETWEEN
Decide salary
for a worker
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Types of Decisions
TYPES OF DECISIONS YOU
FACE

RECURRING DECISIONS - those you make
repeatedly, often periodically.

NONRECURRING DECISIONS - those you
make infrequently, perhaps only once.
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The Decision-Making Process
PHASES OF THE DECISIONMAKING PROCESS
1.
2.
3.
4.
INTELLIGENCE -Find what to fix
DESIGN - Find fixes
CHOICE - Pick a fix
IMPLEMENTATION - Apply the fix
See Figure 5.3
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IT Brainpower
TYPES OF IT BRAINPOWER
Decision Support Systems (DSS)
 Group Decision Support Systems (GDSS)
 Geographic Information Systems (GIS)
 Artificial Intelligence Systems (AI)

–
–
–
–
Expert Systems
Neural Networks
Genetic Algorithms
Intelligent Agents
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DSS
A DECISION SUPPORT SYSTEM
(DSS)
is a highly flexible and interactive IT system
that is designed to support decision making
when the problem is not structured.
A DSS assists you in making a decision, as
opposed to making the decision for you.
See Figure 5.4
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DSS
A DSS Can Help With Analysis
Tasks Like
Deciding where to spend advertising
dollars
 Analyzing sales trend information
 Analyzing drug interactions
 Developing airline schedules
 Pricing products
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DSS
A DSS Has Three Components
DATA MANAGEMENT - to allow you to
store and access information.
 MODEL MANAGEMENT - to allow you
to store and access models.
 USER INTERFACE MANAGEMENT to allow you to easily manipulate
information and models.
See Figure 5.5

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DSS
STEPS IN DEVELOPING A DSS
1.INTELLIGENCE
– Do you need a DSS?
– What should it do?
– What does it need?
2.DESIGN
– What can you buy/build?
3.CHOICE
Commercial Package
DSS Generator:Excel,Quatro Pro
Programming Language
– What will you buy/build?
4.IMPLEMENTATION
– Build or install DSS
– Learn, test, and evaluate the DSS
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GDSS
A GROUP DECISION SUPPORT
SYSTEM (GDSS)
is a type of decision support system that
facilitates the formulation of and solution to
problems by a team.
A GDSS helps a team to generate ideas,
identify strengths and weaknesses, choose
an alternative, and reach a consensus.
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GDSS
A GDSS Can Help With Team
Tasks Like
Determining new product design
 Evaluating the impact of new
competition
 Formulating a strategic plan
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GDSS
THE STEPS OF GROUP
DECISION MAKING
1.Brainstorming - generate ideas
2.Issue Categorization and Analysis classify ideas
3.Ranking and Voting - prioritize
alternatives, reach consensus
See Figure 5.9
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GDSS
PEOPLE IN A GDSS
Team: People united by a common goal
 GDSS facilitator has two roles

– Nontechnical: run the meeting
– Technical: operate IT components
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GDSS
IT TOOLS IN A GDSS
Groupware - software than enables
team work
 DSS Capabilities - software that
enables team decision making
 Telecommunications - hardware and
software that connect computers

JoinNet Groupware Support Decision Making
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GDSS
MEETINGS WHEN AND WHERE
YOU WANT TO BE

Same-Time (Synchronous) Meetings




In the same room
In the same city
On the same planet
Different-Time (Asynchronous) Meetings


In the same city
On the same planet
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GDSS
A GEOGRAPHIC INFORMATION
SYSTEM (GIS)
is a decision support system designed
specifically to work with spatial information.
A GIS represents information thematically in
overlapping layers, each of which shows a
different aspect of the total picture.
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GDSS
A GIS Can Help With Spatial
Analysis Tasks Like
Identifying the best site to locate a branch
office
 Targeting pockets of potential customers
 Repositioning promotions and advertising
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AI
ARTIFICIAL INTELLIGENCE (AI)
is the science of making machines imitate
human thinking and behavior.
AI helps machines perform tasks that require
complex and varying sets of steps such as
retrieving debris from the ocean floor.
AI SYSTEMS ARE USED IN
Finance analysis
 hospital
 government agencies
 credit card companies


Robots are mechanical device equipped
with simulated human senses and the
capability of taking action on its own.
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AI
TYPES OF AI USED IN
BUSINESS
EXPERT SYSTEMS
 NEURAL NETWORKS
 GENETIC ALGORITHMS
 INTELLIGENT AGENTS

70% of the top 500 companies use AI as part of
decision support.
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Expert System
AN EXPERT SYSTEM
is an artificial intelligence system that
applies reasoning capabilities to reach a
conclusion.
An expert system captures expertise from a
human expert and applies it to a problem.
Expert systems are excellent for diagnostic
and prescriptive problems.
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Expert System
An Expert System Can Perform
Diagnostic and Prescriptive
Tasks Like
Auditing and tax planning
 Diagnosing illnesses
 Managing forest resources

Hennery Expert System
Hennery Expert System
Hennery Expert System
Paddyfield Expert System
Paddyfield Management Expert System
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Expert System
COMPONENTS OF AN EXPERT
SYSTEM
Information
People
IT
Components
How do these components fit together?
See the traffic light example.
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Expert System
INFORMATION TYPES IN AN
EXPERT SYSTEM
Domain Expertise - the set of steps that will
solve the problem.
 “Why”s Information - the information that
explains the expert system‘s actions.
 Problem Facts - specific information
concerning the current problem.
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Expert System
PEOPLE IN AN EXPERT SYSTEM
Domain Expert - the person who knows how
to solve the problem without the aid of IT.
 Knowledge Engineer - the person who builds
the expert system.
 Knowledge Worker - the person who uses the
expert system to solve a problem.
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Expert System
IT COMPONENTS IN AN EXPERT
SYSTEM

KNOWLEDGE BASE - stores the domain
expertise.

INFERENCE ENGINE - processes the domain
expertise and your problem facts to reach a
conclusion.
RULES IN VP EXPERT
RULE flu
IF throat = sore
AND temperature = high
OR temperature = very_high
THEN Diagnosis = flu
BECAUSE "High temperature indicates a
possible flu, and a sore throat would confirm
it.";
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Expert System
IT COMPONENTS IN AN EXPERT
SYSTEM

KNOWLEDGE ACQUISITION - used by the
knowledge engineer to build the expert
system.

USER INTERFACE - used to run a
consultation.

EXPLANATION MODULE - stores the why
information.
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Expert System
TO ACQUIRE AN EXPERT
SYSTEM
Buy an off-the-shelf expert system
 Use an expert system shell
 Develop an expert system from
scratch

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Expert System
WHAT EXPERT SYSTEMS CAN
DO
• Handle massive
amounts of
information
• Reduce errors
• Improve customer
service
•Provide consistency
in decision making
•Provide new
information
•Reduce costs
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Expert System
WHAT EXPERT SYSTEMS CAN’T
DO
Handle all types of domain expertise
 Solve problems other than those for which
they are designed
 Apply common sense or judgment to a
problem
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Neural Network
A NEURAL NETWORK
is an artificial intelligence system which is
capable of learning because it‘s patterned
after the human brain.
A neural network simulates the human ability to
classify things based on the experience of seeing
many examples.
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Neural Network
A Neural Network Can Perform
Pattern Recognition Tasks Like
Distinguishing different chemical
compounds
 Detecting anomalies in human tissue
that may signify disease
 Reading handwriting
 Detecting fraud in credit card use

NN works best on pattern-recognition
problems for which a vast amount of
historical information is available.
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Genetic Algorithm
A GENETIC ALGORITHM
is an artificial intelligence system that mimics
the evolutionary, survival-of-the-fittest
processes to generate increasingly better
solutions to a problem.
Genetic algorithms produce several generations
of solutions, choosing the best of the current set
for each new generation.
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Genetic Algorithm
A Genetic Algorithm Can
Generate Lots of Solutions As In
Generating human faces based on a few
known features.
 Generating solutions to routing problems.
 Generating stock portfolios.
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Genetic Algorithm
THE CONCEPTS OF EVOLUTION
IN GENETIC ALGORITHMS
SELECTION - or survival of the fittest. The
key is to give preference to better outcomes.
 CROSSOVER - combining portions of good
outcomes in the hope of creating an even
better outcome.
 MUTATION - randomly trying combinations
and evaluating the success (or failure) of the
outcome.
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Intelligent Agent
AN INTELLIGENT AGENT
is an artificial intelligence system that can move
around your computer or network performing
repetitive tasks independently, adapting itself to
your preferences.
An intelligent agent is like a travel agent in that it
performs tasks that you stipulate.
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Intelligent Agent
An Intelligent Agent Can Perform
Tasks Like
Acting as a personal electronic assistant
to collect, send, and prioritize electronic
information such as e-mail.
 Finding and retrieving information from a
database.
 Finding and retrieving information across
networks.
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Intelligent Agent
How Does an Intelligent Agent
Do That?
An intelligent agent (usually) combines the
capabilities of two or more of the most modern
software technologies such as expert systems,
neural networks, genetic algorithms, objectoriented programming, and so on.
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AI
Based On
Starting
Information
AI System
Problem Type
Expert
Systems
Diagnostic or
prescriptive
Strategies of
experts
Expert抯
know-how
Neural
Networks
Identification,
classification,
prediction
The human
brain
Acceptable
patterns
Genetic
Algorithms
Biological
Optimal solution evolution
Set of
possible
solutions
Intelligent
Agents
Specific and
repetitive tasks
Your
preferences
One or more AI
techniques
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IT Brainpower
AI SYSTEMS CAN BE COMBINED
WITH DECISION SUPPORT
SYSTEMS
DSSs can incorporate one or more expert
systems creating an intelligent DSS, a
DSS/ES, or a knowledge-based DSS.
 Neural networks can be combined with GISs
to apply pattern recognition capabilities to
spatial information.
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IT Brainpower
A HYBRID INTELLIGENT
SYSTEM
is an IT system which combines two or more
artificial intelligence systems.
Neural networks and expert systems can be
combined to create a 搕rainable?expert
system.
 Neural networks and genetic algorithms can
be combined to train neural networks.

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TO SUMMARIZE

IT can help you be an effective decision maker
by assisting you in decision-making tasks with
– Decision support systems (DSS)
– Group decision support systems (GDSS)
– Geographic information systems (GIS)
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TO SUMMARIZE

IT can help you be an effective decision maker
by performing tasks for you with AI using
–
–
–
–
Expert systems
Neural networks
Genetic algorithms
Intelligent agents
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TO SUMMARIZE

To benefit from the decision support
capabilities of IT you must know
– The nature of the problem
– What type of decision support tools can help
– How to apply the decision support tools to the problem.