McGraw-Hill/Irwin ©2005 The McGraw-Hill Companies, All rights reserved

CHAPTER 4

DECISION SUPPORT AND ARTIFICIAL

INTELLIGENCE

Brainpower for Your Business

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INTRODUCTION

• Computer-aided decision support

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DECISIONS, DECISIONS, DECISIONS

• Phases of decision making

– Intelligence – find or recognize a problem, need,

or opportunity

– Design – consider possible ways of solving the

problem

– Choice – weigh the merits of each solution

– Implementation – carry out the solution

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Four Phases of Decision Making

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Types of Decisions You Face

• Structured decision – processing a certain

information in a specified way so that you will

always get the right answer

• Nonstructured decision – one for which

there may be several “right” answers, without

a sure way to get the right answer

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What Job Do I Take?

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Types of Decisions You Face

• Recurring decision – one that happens

repeatedly

• Nonrecurring (ad hoc) decision – one you

make infrequently

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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

• Decision support systems help you analyze, but you must know how to solve the problem, and how to use the results of the analysis

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Alliance between You and a DSS

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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

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Components of a DSS

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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 information, generate business intelligence, and make decisions

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San Diego in GIS Software

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ARTIFICIAL INTELLIGENCE

• Artificial intelligence (AI) – the science of

making machines imitate human thinking and

behavior

• Robot – a mechanical device equipped with

simulated human senses and the ability to

take action on its own

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ARTIFICIAL INTELLIGENCE

• Types of AI systems used in business

– Expert systems

– Neural networks

– Genetic algorithms

– Intelligent agents

• AI systems deliver the conclusion (rather than

helping you analyze the options)

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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?)

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Traffic Light Expert System

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Components of an Expert System

1. Information Types

– Domain expertise – how to solve the problem

– “Why?” information – explains the questions

– Problem facts – the current situation

2. People

– Domain expert – the expert in that field

– Knowledge engineer – the computer expert

– Knowledge worker – the user

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Components of an Expert System

3. IT Components

• Knowledge acquisition – used to enter rules

• Explanation module – where explanations are kept

• User interface – the part the user uses

• Inference engine – applies the logic

• Knowledge base – where rules are kept

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Developing and Using an Expert

System

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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

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NEURAL NETWORKS

• Neural network (artificial neural network

or ANN) – an artificial intelligence system

that is capable of finding and differentiating

patterns

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The Layers of a Neural Network

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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

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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

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Evolutionary Principles of Genetic

Algorithms

1. Selection – or survival of the fittest or

giving preference to better outcomes

2. Crossover – combining portion of good

outcomes to create even better outcomes

3. Mutation – randomly trying combinations

and evaluating the success of each

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Genetic Algorithms Can…

• Take thousands or even millions of possible

solutions and combining and recombining

them until it finds the optimal solution

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INTELLIGENT AGENTS

• Intelligent agent – software that assists you,

or acts on your behalf, in performing

repetitive computer-related tasks

– Buyer agents or shopping bots

– User or personal agents

– Monitoring-and surveillance agents

– Data-mining agents

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Buyer Agents

• Buyer agent or shopping bot – an

intelligent agent on a Web sites that helps

you, the customer, find products and services

you want

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User Agents

• User agent 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

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Monitoring-and-Surveillance Agents

• Monitoring-and-surveillance (predictive)

agents – intelligent agents that observe and

report on equipment.

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Data-Mining Agents

• Data-mining agent – operates in a data

warehouse discovering information