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Transcript
Chapter 4 Decision Support and Artificial Intelligence McGraw-Hill/Irwin © 2008 The McGraw-Hill Companies, All Rights Reserved STUDENT LEARNING OUTCOMES 1. Define decision support system, list its components, and identify the type of application it’s suited to. 2. Define geographic information systems and state how they differ from other decision support systems. 4-2 STUDENT LEARNING OUTCOMES 3. Define artificial intelligence and list the different types that are used in businesses. 4. Define expert systems and describe the types of problems to which they are applicable. 4-3 STUDENT LEARNING OUTCOMES 5. Define neural networks and fuzzy logic and the uses of these AI tools. 6. Define genetic algorithms and list the concepts on which they are based and the types of problems they solve. 4-4 STUDENT LEARNING OUTCOMES 7. Define intelligent agents and list the different types that are used in businesses. 8. Define agent-based modeling and swarm intelligence. 4-5 Decision Support System – The Resident Opinion • Cleveland Clinic uses automated DSSs when diagnosing patient illnesses • All hospital databases are tied together, making it possible for doctors to compare each new illness and patient with all relevant previous cases 4-6 Decision Support System – The Resident Opinion • By being able to compare data on illnesses as well as other data such as demographics, the clinic can better pinpoint the best treatment • The computer-aided decision support that the Cleveland Clinic uses includes data-mining and neural network techniques 4-7 Decision Support System – The Resident Opinion • Class poll… – What IT concepts can you identify for the Cleveland Clinic? – Do you foresee a health care system where you’d do most of the diagnosis and arrange the treatments yourself with/through IT? – Is there a downside to predicting which patients are more likely to fall victim to specific diseases? (Hint: You might think about what you learned in you statistics courses.) 4-8 INTRODUCTION • Computer-aided decision support 4-9 DECISIONS, DECISIONS, DECISIONS • Phases of decision making 1. 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 4-10 Four Phases of Decision Making 4-11 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 • Sometimes you satisfice – make a decision that is satisfactory but not necessarily the best 4-12 What Job Do I Take? 4-13 Types of Decisions You Face • Recurring decision – one that happens repeatedly • Nonrecurring (ad hoc) decision – one you make infrequently 4-14 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 4-15 Alliance between You and a DSS 4-16 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 4-17 Components of a DSS 4-18 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 4-19 San Diego in GIS Software 4-20 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 4-21 ARTIFICIAL INTELLIGENCE • Types of AI systems used in business 1. 2. 3. 4. Expert systems Neural networks Genetic algorithms Intelligent agents • AI systems deliver the conclusion (rather than helping you analyze the options) 4-22 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?) 4-23 Traffic Light Expert System 4-24 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 4-25 NEURAL NETWORKS AND FUZZY LOGIC • Neural network (artificial neural network or ANN) – an artificial intelligence system that is capable of finding and differentiating patterns 4-26 Layers of a Neural Network 4-27 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 4-28 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 4-29 GENETIC ALGORITHMS • Genetic algorithm – an artificial intelligence system that mimics the evolutionary, survivalof-the-fittest process to generate increasingly better solutions to a problem 4-30 Evolutionary Principles of Genetic Algorithms 1. 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 4-31 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 4-32 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 4-33 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 4-34 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 4-35 Data-Mining Agents Data-mining agent – operates in a data warehouse discovering information 4-36 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 4-37 MULTI-AGENT SYSTEMS AND AGENT-BASED MODELING • Biomimicry – learning from ecosystems and adapting their characteristics to human and organizational situations • Used to 1. 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 4-38 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 4-39 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 4-40 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 4-41 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 4-42 Ants A and B Leave the Same Point to Search for Food and Leave Trails 4-43 Ant A Finds a Food Source First and Returns to the Nest Leaving a Trail 4-44 Other Ants Follow Ant A’s Trail and Ant B’s Trail Evaporates 4-45 CAN YOU… 1. Define decision support system, list its components, and identify the type of application it’s suited to. 2. Define geographic information systems and state how they differ from other decision support systems. 3. Define artificial intelligence and list the different types that are used in businesses. 4-46 CAN YOU… 4. Define expert systems and describe the types of problems to which they are applicable. 5. Define neural networks and fuzzy logic and the uses of these AI tools. 6. Define genetic algorithms and list the concepts on which they are based and the types of problems they solve. 4-47 CAN YOU… 7. Define intelligent agents and list the different types that are used in businesses. 8. Define agent-based modeling and swarm intelligence. 4-48