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Chapter 4Decision Support and Artificial Intelligence: Brainpower for Your Business
Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin
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STUDENT LEARNING OUTCOMES1. 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.
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STUDENT LEARNING OUTCOMES4. 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.
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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
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AN NFL TEAM NEEDS MORE THAN ATHLETIC ABILITY1. 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?
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INTRODUCTION
Phases of decision making1. 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
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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
Recurring decision – happens repeatedly Nonrecurring (ad hoc) decision – one you
make infrequently
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Types of Decisions You Face
EASIESTEASIEST
MOST MOST DIFFICULTDIFFICULT
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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
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CHAPTER ORGANIZATION
5. Genetic Algorithms Learning outcome #4
6. Intelligent Agents Learning outcome #5
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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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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
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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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Zillow GIS Software for Denver
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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)
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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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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 AND FUZZY LOGIC Neural network (artificial neural network or
ANN) – an artificial intelligence system that is capable of finding and differentiating patterns
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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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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 Google’s search engine Washing machines Antilock breaks
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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 Algorithms1. 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
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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
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INTELLIGENT AGENTS
Intelligent agent – software that assists you, or acts on your behalf, in performing repetitive computer-related tasks
Types Information agents Monitoring-and-surveillance or predictive agents Data-mining agents User or personal agents
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Information Agents
Information Agents – intelligent agents that search for information of some kind and bring it back
Ex: Buyer agent or shopping bot – an intelligent agent on a Web site that helps you, the customer, find products and services you want
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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
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Data-Mining Agents
Data-mining agent – operates in a data warehouse discovering information
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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
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MULTI-AGENT SYSTEMS AND AGENT-BASED MODELING Biomimicry – learning from ecosystems
and adapting their characteristics to human and organizational situations
Used to1. 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
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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
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Business Applications
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
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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
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Characteristics of Swarm Intelligence Flexibility – adaptable to change Robustness – tasks are completed even if
some individuals are removed Decentralization – each individual has a
simple job to do
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