Decision Models and Intelligent

natureplaygroundAI and Robotics

Nov 14, 2013 (3 years and 4 months ago)


Introduction to Managerial Support Systems

Decision Models and Intelligent

Learning Objectives

Describe the concepts of management, decision making, and
computerized support for decision making

Describe decision models and the benefits of computer supported
decision making and experimentation

Define a decision support system (DSS) and the types of problems
with which they are associated

Describe data visualization and explain geographical information
systems and virtual reality

Describe artificial intelligence (AI)

Define an expert system and identify its components

Describe natural language processing and natural language

Managers and Decision Making

Management is a process by which an organization achieves
its goals through the use of resources (people, money, energy,
materials, space, and time)

Resources are inputs, achieving goals is output, and a
manager’s success is often measured by the ratio between
inputs and outputs (productivity, profit, return on
investment, return on assets, etc.) for which they are

Managers and Decision Making

Managers have three basic roles:

Interpersonal roles

figurehead, leader, liaison

Informational roles

monitor, disseminator, spokesperson

Decisional roles

disturbance handler, resource allocator,

Early information systems primarily supported the
informational roles

In this discussion we focus on more recent developments
where IT supports decisional roles

Decision Model Examples

Models are representations of problems

They vary by degree of abstraction:

Iconic (scale)

least abstract


Mathematical (quantitative)


most abstract

Benefits of Computer Supported
Decision Systems

Cost of virtual experimentation is lower

Compresses time

Manipulations are easier

Cost of mistakes is lower

Can evaluate risk and uncertainty

Can compare a large number of alternatives

Can be used for training

Why Managers Need IT Support

It is difficult to make good decisions without valid and
relevant information

Despite widespread information availability, making decisions
is becoming increasingly difficult due to the following trends:

Number of alternatives is increasing

Time pressure

Increased uncertainty

Need to rapidly access remote information, consult with
experts, or conduct a group decision
making session

Different IT solutions are needed depending on the problem
structure and the nature of decision

Decision Support Framework

Decision Support Systems

Decision support systems (DSS) combine models and data in
an attempt to solve semi
structured and some unstructured
problems with extensive user involvement

Models are simplified representations, or abstractions, of

In the following we discuss several DSS components and
applications to illustrate some of the capabilities of these

Geographic Information Systems

A geographic information system (GIS) is a computer
system for capturing, integrating, manipulating, and
displaying data using digitized maps

Its most distinguishing characteristic is that every record or
digital object has an identified geographical location

What are some current GIS applications?

Virtual Reality

There is no standard definition of virtual reality

The most common definitions usually describe virtual reality
(VR) as interactive, computer
generated, three
graphics delivered to the user through a head

In VR, a person “believes” that what they are doing is real
even though it is artificially created

What are some current VR applications?

Intelligent Systems

Intelligent systems is a term that best describes the various
commercial applications of artificial intelligence

Artificial intelligence (AI) is a subfield of computer science
that is concerned with studying the thought processes of
humans and re
creating the effects of those processes via
machines, such as computers and robots

AI’s ultimate goal is to build machines that will mimic human

An interesting test to determine whether a computer
exhibits intelligent behavior was designed by Alan Turing (the
Turing test)

Comparison of the Capabilities of
Natural versus Artificial Intelligence


Natural Intelligence

Artificial Intelligence

Preservation of knowledge




and sharing of

Difficult, expensive, takes time

Easy, fast, and cheap

when in
the right format

Total cost of knowledge

Can be erratic and inconsistent

Consistent and thorough


of knowledge

Difficult, expensive

Fairly easy, inexpensive


Can be very high

Low, uninspired

Use of sensory experiences

Direct and rich in possibilities


Recognizing patterns and

Fast, easy to explain

Getting better, but not as good
as humans


Makes use of a wide range of

Good only in narrow, focused,
stable domains

Expert Systems

When an organization has a complex decision to make or problem
to solve, it often turns to experts for advice

Expert systems (ESs) are computer systems that attempt to mimic
human experts by applying expertise in a specific domain

The transfer of expertise from an expert to a computer and then
to the user involves four activities:

Knowledge acquisition

Knowledge representation


Knowledge transfer

What are some current ES applications?

Expert System Structure

Natural Language Processing and

Voice Technologies

Natural language processing (NLP) refers to communicating
with a computer in the user’s native language

Why is this a complex task?

Two types of NLP include:

Natural language understanding (or speech recognition)

Allows a computer to comprehend spoken instructions given in the user’s
everyday language

It’s easy to use, faster than typing, and provides manual freedom

Natural language generation (or voice synthesis)

Enables computers to produce everyday language as voice or text

Sounds are constructed from basic pre
recorded sound components

What are some voice technology applications?