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Influence Diagram: Bayesian Network, Bayesian Inference, Decision Making, Expected Utility Hypothesis, Decision Analysis, Decision Tree, Exponential Growth, Game Theory - Softcover
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Influence Diagram
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 80 pp. Englisch. Bestandsnummer des Verkäufers 9786131713019
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Influence Diagram : Bayesian Network, Bayesian Inference, Decision Making, Expected Utility Hypothesis, Decision Analysis, Decision Tree, Exponential Growth, Game Theory
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. An influencediagram (ID) (also called a decision diagram or a decision network) is acompact graphical and mathematical representation of a decisionsituation. It is a generalization of a Bayesian network, in which notonly probabilistic inference problems but also decision making problems(following maximum expected utility criterion) can be modeled andsolved. ID was first developed in mid-1970s within the decision analysiscommunity with an intuitive semantic that is easy to understand. It isnow adopted widely and becoming an alternative to decision tree whichtypically suffers from exponential growth in number of branches witheach variable modeled. ID is directly applicable in team decisionanalysis, since it allows incomplete sharing of information among teammembers to be modeled and solved explicitly. Extension of ID also findits use in game theory as an alternative representation of game tree. Bestandsnummer des Verkäufers 9786131713019
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Influence Diagram
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. An influencediagram (ID) (also called a decision diagram or a decision network) is acompact graphical and mathematical representation of a decisionsituation. It is a generalization of a Bayesian network, in which notonly probabilistic inference problems but also decision making problems(following maximum expected utility criterion) can be modeled andsolved. ID was first developed in mid-1970s within the decision analysiscommunity with an intuitive semantic that is easy to understand. It isnow adopted widely and becoming an alternative to decision tree whichtypically suffers from exponential growth in number of branches witheach variable modeled. ID is directly applicable in team decisionanalysis, since it allows incomplete sharing of information among teammembers to be modeled and solved explicitly. Extension of ID also findits use in game theory as an alternative representation of game tree.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch. Bestandsnummer des Verkäufers 9786131713019
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