Neuware - Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important.Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic-but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar 'assertional' style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.Topics and features:\* Presents a general semantics for both probability and demonic nondeterminism, including abstraction and data refinement\* Introduces readers to the latest mathematical research in rigorous formalization of randomized (probabilistic) algorithms \* Illustrates by example the steps necessary for building a conceptual model of probabilistic programming 'paradigm'\* Considers results of a large and integrated research exercise (10 years and continuing) in the leading-edge area of 'quantitative' program logics\* Includes helpful chapter-ending summaries, a comprehensive index, and an appendix that explores alternative approachesThis accessible, focused monograph,written by international authorities on probabilistic programming, develops an essential foundation topic for modern programming and systems development. Researchers, computer scientists, and advanced undergraduates and graduates studying programming or probabilistic systems will find the work an authoritative and essential resource text.

Bestandsnummer des Verk�ufers 9780387401157

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Titel: Abstraction, Refinement and Proof for Probabilistic Systems
Verlag: Springer New York Nov 2004
Erscheinungsjahr: 2004
Sprache: Englisch
ISBN-10: 0387401156
ISBN-13: 9780387401157
Einband: Buch
Zustand: Neu
Abmessungen: Breite: 243 mm, H�he: 164 mm, Tiefe: 25 mm
Gewicht: 734 Gramm

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Illustrates by example the typical steps necessary in computer science to build a mathematical model of any programming paradigm .

Presents results of a large and integrated body of research in the area of 'quantitative' program logics.

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Probabilistic techniques are increasingly being employed in computer programs and systems because they can increase efficiency in sequential algorithms, enable otherwise nonfunctional distribution applications, and allow quantification of risk and safety in general. This makes operational models of how they work, and logics for reasoning about them, extremely important.

Abstraction, Refinement and Proof for Probabilistic Systems presents a rigorous approach to modeling and reasoning about computer systems that incorporate probability. Its foundations lie in traditional Boolean sequential-program logic—but its extension to numeric rather than merely true-or-false judgments takes it much further, into areas such as randomized algorithms, fault tolerance, and, in distributed systems, almost-certain symmetry breaking. The presentation begins with the familiar "assertional" style of program development and continues with increasing specialization: Part I treats probabilistic program logic, including many examples and case studies; Part II sets out the detailed semantics; and Part III applies the approach to advanced material on temporal calculi and two-player games.

Topics and features:

* Presents a general semantics for both probability and demonic nondeterminism, including abstraction and data refinement

* Introduces readers to the latest mathematical research in rigorous formalization of randomized (probabilistic) algorithms * Illustrates by example the steps necessary for building a conceptual model of probabilistic programming "paradigm"

* Considers results of a large and integrated research exercise (10 years and continuing) in the leading-edge area of "quantitative" program logics

* Includes helpful chapter-ending summaries, a comprehensive index, and an appendix that explores alternative approaches

This accessible, focused monograph, written by international authorities on probabilistic programming, develops an essential foundation topic for modern programming and systems development. Researchers, computer scientists, and advanced undergraduates and graduates studying programming or probabilistic systems will find the work an authoritative and essential resource text.

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