Chapter 4 Decision Support and Artificial Intelligence: Brainpower for Your Business Copyright © 2010 by the McGraw-Hill Companies, Inc. All rights reserved. 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 2. Design 3. Choice 4. Implementation 4-6

Four Phases of Decision Making 4-7

Types of Decisions You Face  Structured decision  Nonstructured decision  Recurring decision  Nonrecurring (ad hoc) decision 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) 4-12

Alliance between You and a DSS 4-13

Components of a DSS  Model management component  Data management component  User interface management component 4-14

Components of a DSS 4-15

Predictive Analytics  Analytics (predictive analytics) 4-16

GEOGRAPHIC INFORMATION SYSTEMS  Geographic information system (GIS) 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 4-19

EXPERT SYSTEMS  Expert (knowledge-based) system 4-20

Traffic Light Expert System 4-21

What Expert Systems Can and Can’t Do  An expert system can  An expert system can’t  4-22

NEURAL NETWORKS AND FUZZY LOGIC  Neural network (artificial neural network or ANN)  4-23

Neural Networks Can…  4-24

Fuzzy Logic  Fuzzy logic 4-25

GENETIC ALGORITHMS  Genetic algorithm 4-26

Evolutionary Principles of Genetic Algorithms 1. Selection 2. Crossover 3. Mutation

Genetic Algorithms Can… 4-28

INTELLIGENT AGENTS  Intelligent agent  Types 4-29

Information Agents  Information Agents  Ex: Buyer agent or shopping bot 4-30

Monitoring-and-Surveillance Agents  Monitoring-and-surveillance (predictive) agents 4-31

Data-Mining Agents  Data-mining agent 4-32

User Agents  User or personal agent  Examples: 4-33

MULTI-AGENT SYSTEMS AND AGENT-BASED MODELING  Biomimicry 4-34

Agent-Based Modeling  Agent-based modeling  Multi-agent system 4-35

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 4-36

Swarm Intelligence  Swarm (collective) intelligence 4-37

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 4-38