Advances in the Dempster-Shafer Theory of Evidence PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Advances in the Dempster-Shafer Theory of Evidence PDF full book. Access full book title Advances in the Dempster-Shafer Theory of Evidence by Ronald R. Yager. Download full books in PDF and EPUB format.
Author: Ronald R. Yager
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 616
Get Book Here
Book Description
Builds on classical probability theory and offers an extremely workable solution to the many problems of artificial intelligence, concentrating on the rapidly growing areas of fuzzy reasoning and neural computing. Contains a collection of previously unpublished articles by leading researchers in the field.
Author: Ronald R. Yager
Publisher: John Wiley & Sons
ISBN:
Category : Computers
Languages : en
Pages : 616
Get Book Here
Book Description
Builds on classical probability theory and offers an extremely workable solution to the many problems of artificial intelligence, concentrating on the rapidly growing areas of fuzzy reasoning and neural computing. Contains a collection of previously unpublished articles by leading researchers in the field.
Author: Glenn Shafer
Publisher: Princeton University Press
ISBN: 0691214697
Category : Mathematics
Languages : en
Pages :
Get Book Here
Book Description
Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combination, this book constructs a new theory of epistemic probability. The theory draws on the work of A. P. Dempster but diverges from Depster's viewpoint by identifying his "lower probabilities" as epistemic probabilities and taking his rule for combining "upper and lower probabilities" as fundamental. The book opens with a critique of the well-known Bayesian theory of epistemic probability. It then proceeds to develop an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions. This rule, together with the idea of "weights of evidence," leads to both an extensive new theory and a better understanding of the Bayesian theory. The book concludes with a brief treatment of statistical inference and a discussion of the limitations of epistemic probability. Appendices contain mathematical proofs, which are relatively elementary and seldom depend on mathematics more advanced that the binomial theorem.
Author: Ronald R. Yager
Publisher: Springer
ISBN: 354044792X
Category : Technology & Engineering
Languages : en
Pages : 813
Get Book Here
Book Description
This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.
Author: Thierry Denoeux
Publisher: Springer Science & Business Media
ISBN: 3642294618
Category : Technology & Engineering
Languages : en
Pages : 442
Get Book Here
Book Description
The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories. This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) and applications in various areas including classification, image processing, statistics and intelligent vehicles.
Author: Dov M. Gabbay
Publisher: Springer
ISBN: 9780792351658
Category : Science
Languages : en
Pages : 477
Get Book Here
Book Description
Author: Franz Huber
Publisher: Springer Science & Business Media
ISBN: 1402091982
Category : Philosophy
Languages : en
Pages : 352
Get Book Here
Book Description
This anthology is the first book to give a balanced overview of the competing theories of degrees of belief. It also explicitly relates these debates to more traditional concerns of the philosophy of language and mind and epistemic logic.
Author: Glenn Shafer
Publisher: John Wiley & Sons
ISBN: 1118547934
Category : Business & Economics
Languages : en
Pages : 483
Get Book Here
Book Description
Game-theoretic probability and finance come of age Glenn Shafer and Vladimir Vovk’s Probability and Finance, published in 2001, showed that perfect-information games can be used to define mathematical probability. Based on fifteen years of further research, Game-Theoretic Foundations for Probability and Finance presents a mature view of the foundational role game theory can play. Its account of probability theory opens the way to new methods of prediction and testing and makes many statistical methods more transparent and widely usable. Its contributions to finance theory include purely game-theoretic accounts of Ito’s stochastic calculus, the capital asset pricing model, the equity premium, and portfolio theory. Game-Theoretic Foundations for Probability and Finance is a book of research. It is also a teaching resource. Each chapter is supplemented with carefully designed exercises and notes relating the new theory to its historical context. Praise from early readers “Ever since Kolmogorov's Grundbegriffe, the standard mathematical treatment of probability theory has been measure-theoretic. In this ground-breaking work, Shafer and Vovk give a game-theoretic foundation instead. While being just as rigorous, the game-theoretic approach allows for vast and useful generalizations of classical measure-theoretic results, while also giving rise to new, radical ideas for prediction, statistics and mathematical finance without stochastic assumptions. The authors set out their theory in great detail, resulting in what is definitely one of the most important books on the foundations of probability to have appeared in the last few decades.” – Peter Grünwald, CWI and University of Leiden “Shafer and Vovk have thoroughly re-written their 2001 book on the game-theoretic foundations for probability and for finance. They have included an account of the tremendous growth that has occurred since, in the game-theoretic and pathwise approaches to stochastic analysis and in their applications to continuous-time finance. This new book will undoubtedly spur a better understanding of the foundations of these very important fields, and we should all be grateful to its authors.” – Ioannis Karatzas, Columbia University
Author: David Lee Hall
Publisher: Artech House
ISBN: 9781580533355
Category : Computers
Languages : en
Pages : 470
Get Book Here
Book Description
Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. The latest edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control. data fusion system, this book guides you through the process of determining the trade-offs among competing data fusion algorithms, selecting commercial off-the-shelf (COTS) tools, and understanding when data fusion improves systems processing. Completely new chapters in this second edition explain data fusion system control, DARPA's recently developed TRIP model, and the latest applications of data fusion in data warehousing and medical equipment, as well as defence systems.
Author: J. Dolezal
Publisher: Springer
ISBN: 0387348972
Category : Computers
Languages : en
Pages : 635
Get Book Here
Book Description
Proceedings volume contains carefully selected papers presented during the 17th IFIP Conference on System Modelling and Optimization. Optimization theory and practice, optimal control, system modelling, stochastic optimization, and technical and non-technical applications of the existing theory are among areas mostly addressed in the included papers. Main directions are treated in addition to several survey papers based on invited presentations of leading specialists in the respective fields. Publication provides state-of-the-art in the area of system theory and optimization and points out several new areas (e.g fuzzy set, neural nets), where classical optimization topics intersects with computer science methodology.
Author: George Klir
Publisher: Springer Science & Business Media
ISBN: 9783790812428
Category : Mathematics
Languages : en
Pages : 196
Get Book Here
Book Description
Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory. The volume is organized as follows.
