# Chapter 4: Decision Support and Artificial Intelligence

AI and Robotics

Oct 23, 2013 (4 years and 8 months ago)

108 views

Chapter 4

Decision Support and Artificial
Intelligence: Brainpower for Your

-

McGraw
-
Hill/Irwin

STUDENT LEARNING OUTCOMES

1.
Compare and contrast decision support
systems and geographic information
systems.

2.
Define expert systems and describe the
types of problem to which they are
applicable.

3.
Define neural networks and fuzzy logic and
the use of these AI tools.

4
-
2

STUDENT LEARNING OUTCOMES

4.
Define genetic algorithms and list the
concepts on which they are based and the
types of problems they solve.

5.
Describe the four types of agent
-
based
technologies.

4
-
3

AN NFL TEAM NEEDS MORE
THAN ATHLETIC ABILITY

The Patriots football team is a very
successful one

The team uses a decision support system to
analyze the opposition’s game

The software breaks down the game day
video into plays and player actions

With this information the Patriots can better
formulate their strategy

4
-
4

AN NFL TEAM NEEDS MORE
THAN ATHLETIC ABILITY

1.
DSS with predictive analytics used to gain
the advantage in other sports? Choose a
sport and explain how that might work.

2.
Would allowing coaches to have laptops on
the field change the game appreciably?

3.
What other aspect of football could be
improved by decision support systems?

4
-
5

INTRODUCTION

Phases of decision making

1.
Intelligence

find or recognize a problem, need,
or opportunity

2.
Design

consider possible ways of solving the
problem

3.
Choice

weigh the merits of each solution

4.
Implementation

carry out the solution

4
-
6

Four Phases of Decision Making

4
-
7

Types of Decisions You Face

Structured decision

processing a certain
information in a specified way so that you will

Nonstructured decision

one for which
there may be several “right” answers, without
a sure way to get the right answer

Recurring decision

happens repeatedly

one you
make infrequently

4
-
8

Types of Decisions You Face

EASIEST

MOST
DIFFICULT

4
-
9

CHAPTER ORGANIZATION

1.
Decision Support Systems

Learning outcome #1

2.
Geographic Information Systems

Learning outcome #1

3.
Expert Systems

Learning outcome #2

4.
Neural Networks and Fuzzy Logic

Learning outcome #3

4
-
10

CHAPTER ORGANIZATION

5.
Genetic Algorithms

Learning outcome #4

6.
Intelligent Agents

Learning outcome #5

4
-
11

DECISION SUPPORT SYSTEMS

Decision support system (DSS)

a highly
flexible and interactive system that is
designed to support decision making when
the problem is not structured

but you must know how to solve the problem,
and how to use the results of the analysis

4
-
12

Alliance between You and a DSS

4
-
13

Components of a DSS

Model management component

consists
of both the DSS models and the model
management system

Data management component

stores and
maintains the information that you want your
DSS to use

User interface management component

allows you to communicate with the DSS

4
-
14

Components of a DSS

4
-
15

Predictive Analytics

Analytics (predictive analytics)

highly
computational process of measuring and
predicting customer behavior/attitudes

Uses combination of statistics, probability,
ops management methods, AI tools, data
mining, and predictive modeling

Types

Text

natural language analysis

Content

audio, video, graphical

Web

Web traffic analysis

4
-
16

GEOGRAPHIC INFORMATION
SYSTEMS

Geographic information system (GIS)

DSS designed specifically to analyze spatial
information

Spatial information is any information in map
form

Businesses use GIS software to analyze
and make decisions

4
-
17

Zillow GIS Software for Denver

4
-
18

ARTIFICIAL INTELLIGENCE

DSSs and GISs support decision making; you
are still completely in charge

Artificial intelligence
, the science of making
machines imitate human thinking and
behavior, can replace human decision
making in some instances

Expert systems

Neural networks (and fuzzy logic)

Genetic algorithms

Intelligent agents (or agent
-
based technologies)

4
-
19

EXPERT SYSTEMS

Expert (knowledge
-
based) system

an
artificial intelligence system that applies
reasoning capabilities to reach a conclusion

Used for

Diagnostic problems (what’s wrong?)

Prescriptive problems (what to do?)

4
-
20

Traffic Light Expert System

4
-
21

What Expert Systems Can and
Can’t Do

An expert system can

Reduce errors

Improve customer service

Reduce cost

An expert system can’t

Use common sense

Automate all processes

4
-
22

NEURAL NETWORKS AND FUZZY
LOGIC

Neural network (artificial neural network or
ANN)

an artificial intelligence system that is
capable of finding and differentiating patterns

4
-
23

Neural Networks Can…

Learn and adjust to new circumstances on
their own

Take part in massive parallel processing

Function without complete information

Cope with huge volumes of information

Analyze nonlinear relationships

4
-
24

Fuzzy Logic

Fuzzy logic

a mathematical method of
handling imprecise or subjective information

Used to make ambiguous information such as
“short” usable in computer systems

Applications

Washing machines

Antilock breaks

4
-
25

GENETIC ALGORITHMS

Genetic algorithm

an artificial intelligence
system that mimics the evolutionary, survival
-
of
-
the
-
fittest process to generate increasingly
better solutions to a problem

4
-
26

Evolutionary Principles of
Genetic Algorithms

1.
Selection

or survival of the fittest or giving
preference to better outcomes

2.
Crossover

combining portions of good
outcomes to create even better outcomes

3.
Mutation

randomly trying combinations
and evaluating the success of each

4
-
27

Genetic Algorithms Can…

Take thousands or even millions of possible
solutions and combine and recombine them
until it finds the optimal solution

Work in environments where no model of how
to find the right solution exists

4
-
28

INTELLIGENT AGENTS

Intelligent agent

software that assists you,
or acts on your behalf, in performing
repetitive computer
-

Types

Information agents

Monitoring
-
and
-
surveillance or predictive agents

Data
-
mining agents

User or personal agents

4
-
29

Information Agents

Information Agents

intelligent agents that
search for information of some kind and bring
it back

Ex:

or
shopping bot

an
intelligent agent on a Web site that helps you,
the customer, find products and services you
want

4
-
30

Monitoring
-
and
-
Surveillance
Agents

Monitoring
-
and
-
surveillance (predictive)
agents

intelligent agents that constantly
observe and report on some entity of interest,
a network, or manufacturing equipment, for
example

4
-
31

Data
-
Mining Agents

Data
-
mining agent

operates in a data
warehouse discovering information

4
-
32

User Agents

User
or
personal agent

intelligent agent
that takes action on your behalf

Examples:

Prioritize e
-
mail

Act as gaming partner

Assemble customized news reports

Fill out forms for you

“Discuss” topics with you

4
-
33

MULTI
-
AGENT SYSTEMS AND
AGENT
-
BASED MODELING

Biomimicry

learning from ecosystems
and adapting their characteristics to human
and organizational situations

Used to

1.
Learn how people
-
based systems behave

2.
Predict how they will behave under certain
circumstances

3.
Improve human systems to make them more
efficient and effective

4
-
34

Agent
-
Based Modeling

Agent
-
based modeling

a way of
simulating human organizations using
multiple intelligent agents, each of which
follows a set of simple rules and can adapt to
changing conditions

Multi
-
agent system

groups of intelligent
agents have the ability to work independently
and to interact with each other

4
-
35

Southwest Airlines

cargo routing

P&G

supply network optimization

Air Liquide America

reduce production and
distribution costs

Merck

distributing anti
-
AIDS drugs in Africa

Ford

balance production costs & consumer
demands

Edison Chouest

deploy service and supply
vessels

4
-
36

Swarm Intelligence

Swarm (collective) intelligence

the
collective behavior of groups of simple agents
that are capable of devising solutions to
problems as they arise, eventually learning to
coherent global patterns

4
-
37

Characteristics of Swarm
Intelligence

Flexibility

Robustness