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Chapter 4 DECISION SUPPORT AND ARTIFICIAL INTELLIGENCE Brainpower for Your Business

Chapter 4 DECISION SUPPORT AND ARTIFICIAL INTELLIGENCE Brainpower for Your Business. STUDENT LEARNING OUTCOMES. Compare and contrast decision support systems and geographic information systems. Define expert systems and describe the types of problem to which they are applicable.

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Chapter 4 DECISION SUPPORT AND ARTIFICIAL INTELLIGENCE Brainpower for Your Business

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  1. Chapter 4DECISION SUPPORT AND ARTIFICIAL INTELLIGENCEBrainpower for Your Business

  2. STUDENT LEARNING OUTCOMES • Compare and contrast decision support systems and geographic information systems. • Define expert systems and describe the types of problem to which they are applicable. • Define neural networks and fuzzy logic and the use of these AI tools.

  3. STUDENT LEARNING OUTCOMES • Define genetic algorithms and list the concepts on which they are based and the types of problems they solve. • Describe the four types of agent-based technologies.

  4. VISUALIZING INFORMATION IN MAP FORM FOR DECISION MAKING • Geographic information systems (GISs) allows you to see information spatially, or in map form. • Researchers and scientists used a GIS to map the location of all the debris from the shuttle Columbia • The city of Chattanooga uses a GIS to map the location of its 6,000 trees to help develop a maintenance schedule

  5. VISUALIZING INFORMATION IN MAP FORM FOR DECISION MAKING • The city of Richmond, VA, used a GIS to optimize its 2,500 bus stop locations in its public transportation system • Sometimes, a picture is worth a thousand words • Recall from Chapter 1, the form of information often defines its quality

  6. VISUALIZING INFORMATION IN MAP FORM FOR DECISION MAKING • Do you use Web-based map services to get directions and find the location of buildings? If so, why? • In what ways could real estate agents take advantage of the features of a GIS? • How could GIS software benefit a bank wanting to determine the optimal placements for ATMs?

  7. INTRODUCTION • 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

  8. Four Phases of Decision Making

  9. A second model of decision making is satisficing • Organizations in both private and public sectors are saticficing all the time. “fare price” and “reasonable profit”. “High growth” and “maximum growth”.

  10. 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 * Regarding the frequency of decision • Recurring decision – happens repeatedly • Nonrecurring (ad hoc) decision – one you make infrequently

  11. Types of Decisions You Face

  12. CHAPTER ORGANIZATION • Decision Support Systems • Learning outcome #1 • Geographic Information Systems • Learning outcome #1 • Expert Systems • Learning outcome #2 • Neural Networks and Fuzzy Logic • Learning outcome #3

  13. CHAPTER ORGANIZATION • Genetic Algorithms • Learning outcome #4 • Intelligent Agents • Learning outcome #5

  14. 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

  15. Alliance between You and a DSS

  16. 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

  17. Components of a DSS

  18. 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

  19. Zillow GIS Software for Denver

  20. 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?)

  21. Traffic Light Expert System

  22. 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

  23. NEURAL NETWORKS AND FUZZY LOGIC • Neural network (artificial neural network or ANN) – an artificial intelligence system that is capable of finding and differentiating patterns

  24. 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

  25. 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

  26. 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

  27. Evolutionary Principles of Genetic Algorithms • Selection – or survival of the fittest or giving preference to better outcomes • Crossover – combining portions of good outcomes to create even better outcomes • Mutation – randomly trying combinations and evaluating the success of each

  28. 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

  29. 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

  30. 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

  31. 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

  32. Data-Mining Agents • Data-mining agent – operates in a data warehouse discovering information heftiness

  33. 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

  34. MULTI-AGENT SYSTEMS AND AGENT-BASED MODELING • Biomimicry – learning from ecosystems and adapting their characteristics to human and organizational situations • Used to • Learn how people-based systems behave • Predict how they will behave under certain circumstances • Improve human systems to make them more efficient and effective

  35. Agent-Based Modeling • Multi-agent system – groups of intelligent agents have the ability to work independently and to interact with each other • 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

  36. 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

  37. 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

  38. Characteristics of Swarm Intelligence • Flexibility – adaptable to change • Robustness – tasks are completed even if some individuals are removed forager • Decentralization – each individual has a simple job to do • Self organization

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