Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and influence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also: provides a well-founded practical introduction to Bayesian networks, decision trees and influence diagrams; gives several examples and exercises exploiting the computer systems for Bayesian networks and influence diagrams; gives practical advice on constructing Bayesian networks and influence diagrams from domain knowledge; embeds decision making into the framework of Bayesian networks; presents in detail the currently most efficient algorithms for probability updating in Bayesian networks; discusses a wide range of analyses tools and model requests together with algorithms for calculation of responses; and gives a detailed presentation of the currently most efficient algorithm for solving influence diagrams.
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Destinations, frais et délaisVendeur : Antiquariat Bookfarm, Löbnitz, Allemagne
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 JEN 9780387952598 Sprache: Englisch Gewicht in Gramm: 550. N° de réf. du vendeur 2498618
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Vendeur : Antiquariat Bookfarm, Löbnitz, Allemagne
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 JEN 9780387952598 Sprache: Englisch Gewicht in Gramm: 550. N° de réf. du vendeur 2498631
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Vendeur : Florida Mountain Book Co., Datil, NM, Etats-Unis
Etat : Very Good. Hardcover, [xv], 268 pages. Very Good condition. First printing. Size 9.5"x6.25". "The book emphasizes both the human and the computer side. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language." Book has light handling/shelfwear, spine is sunned, else Fine condition, clean and unmarked. N° de réf. du vendeur 009774
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Vendeur : Florida Mountain Book Co., Datil, NM, Etats-Unis
Etat : Near Fine. Hardcover, [xv], 268 pages. Near Fine condition. Second, corrected printing, 2002. Size 9.5"x6.25". "The book emphasizes both the human and the computer side. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language." Book has light exterior shelfwear, else Fine condition, clean and unmarked. N° de réf. du vendeur 009576
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Etat : Very Good. *Price HAS BEEN REDUCED by 10% until Monday, June 16 (weekend SALE item)* Corrected Printing, 268 pp., Hardcover, minor internal library markings else text clean & binding tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. N° de réf. du vendeur ZB1321285
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