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Author : Hong Xu
Publisher :
ISBN 13 :
Total Pages : 137 pages
Book Rating : 4.:/5 (495 download)
Download or read book Uncertain Reasoning and Decision Analysis Using Belief Functions in the Valuation-based Systems written by Hong Xu and published by . This book was released on 1994 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dov M. Gabbay
Publisher : Springer Science & Business Media
ISBN 13 : 9401717370
Total Pages : 518 pages
Book Rating : 4.4/5 (17 download)
Download or read book Handbook of Defeasible Reasoning and Uncertainty Management Systems written by Dov M. Gabbay and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reasoning under uncertainty is always based on a specified language or for malism, including its particular syntax and semantics, but also on its associated inference mechanism. In the present volume of the handbook the last aspect, the algorithmic aspects of uncertainty calculi are presented. Theory has suffi ciently advanced to unfold some generally applicable fundamental structures and methods. On the other hand, particular features of specific formalisms and ap proaches to uncertainty of course still influence strongly the computational meth ods to be used. Both general as well as specific methods are included in this volume. Broadly speaking, symbolic or logical approaches to uncertainty and nu merical approaches are often distinguished. Although this distinction is somewhat misleading, it is used as a means to structure the present volume. This is even to some degree reflected in the two first chapters, which treat fundamental, general methods of computation in systems designed to represent uncertainty. It has been noted early by Shenoy and Shafer, that computations in different domains have an underlying common structure. Essentially pieces of knowledge or information are to be combined together and then focused on some particular question or domain. This can be captured in an algebraic structure called valuation algebra which is described in the first chapter. Here the basic operations of combination and focus ing (marginalization) of knowledge and information is modeled abstractly subject to simple axioms.
Author : SRI International. Artificial Intelligence Center
Publisher :
ISBN 13 :
Total Pages : 60 pages
Book Rating : 4.:/5 (221 download)
Download or read book Decision Analysis Using Belief Functions written by SRI International. Artificial Intelligence Center and published by . This book was released on 1989 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: We prove that it yields expected values identical to those obtained by a probabilistic analysis that makes the same assumption. We maintain a strict separation between evidence that carries information about a situation and assumptions that may be made for disambiguation of choices. In addition, we show how the decision analysis methodology frequently employed in probabilistic reasoning can be extended for use with belief functions. This generalization of decision analysis allows the use of belief functions within the familiar framework of decision trees."
Author : Fabio Cuzzolin
Publisher : Springer Nature
ISBN 13 : 3030631532
Total Pages : 850 pages
Book Rating : 4.0/5 (36 download)
Download or read book The Geometry of Uncertainty written by Fabio Cuzzolin and published by Springer Nature. This book was released on 2020-12-17 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned. In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain associated with modelling uncertainty using belief functions, in an attempt to provide a self-contained manual for the working scientist. In addition, the book proposes in Chap. 5 what is possibly the most detailed compendium available of all theories of uncertainty. Part II, The Geometry of Uncertainty, is the core of this book, as it introduces the author’s own geometric approach to uncertainty theory, starting with the geometry of belief functions: Chap. 7 studies the geometry of the space of belief functions, or belief space, both in terms of a simplex and in terms of its recursive bundle structure; Chap. 8 extends the analysis to Dempster’s rule of combination, introducing the notion of a conditional subspace and outlining a simple geometric construction for Dempster’s sum; Chap. 9 delves into the combinatorial properties of plausibility and commonality functions, as equivalent representations of the evidence carried by a belief function; then Chap. 10 starts extending the applicability of the geometric approach to other uncertainty measures, focusing in particular on possibility measures (consonant belief functions) and the related notion of a consistent belief function. The chapters in Part III, Geometric Interplays, are concerned with the interplay of uncertainty measures of different kinds, and the geometry of their relationship, with a particular focus on the approximation problem. Part IV, Geometric Reasoning, examines the application of the geometric approach to the various elements of the reasoning chain illustrated in Chap. 4, in particular conditioning and decision making. Part V concludes the book by outlining a future, complete statistical theory of random sets, future extensions of the geometric approach, and identifying high-impact applications to climate change, machine learning and artificial intelligence. The book is suitable for researchers in artificial intelligence, statistics, and applied science engaged with theories of uncertainty. The book is supported with the most comprehensive bibliography on belief and uncertainty theory.
Author : David Heckerman
Publisher : Morgan Kaufmann
ISBN 13 : 1483214516
Total Pages : 554 pages
Book Rating : 4.4/5 (832 download)
Download or read book Uncertainty in Artificial Intelligence written by David Heckerman and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
Author : Thomas D. Nielsen
Publisher : Springer
ISBN 13 : 3540450629
Total Pages : 619 pages
Book Rating : 4.5/5 (44 download)
Download or read book Symbolic and Quantitative Approaches to Reasoning with Uncertainty written by Thomas D. Nielsen and published by Springer. This book was released on 2004-04-07 with total page 619 pages. Available in PDF, EPUB and Kindle. Book excerpt: The refereed proceedings of the 7th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2003, held in Aalborg, Denmark in July 2003. The 47 revised full papers presented together with 2 invited survey articles were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on foundations of uncertainty concepts, Bayesian networks, algorithms for uncertainty inference, learning, decision graphs, belief functions, fuzzy sets, possibility theory, default reasoning, belief revision and inconsistency handling, logics, and tools.
Author : Ronald R. Yager
Publisher : Springer
ISBN 13 : 354044792X
Total Pages : 813 pages
Book Rating : 4.5/5 (44 download)
Download or read book Classic Works of the Dempster-Shafer Theory of Belief Functions written by Ronald R. Yager and published by Springer. This book was released on 2008-01-22 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Rajendra P. Srivastava
Publisher : Physica
ISBN 13 : 3790817988
Total Pages : 356 pages
Book Rating : 4.7/5 (98 download)
Download or read book Belief Functions in Business Decisions written by Rajendra P. Srivastava and published by Physica. This book was released on 2013-11-11 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on applications of belief functions to business decisions. Section I introduces the intuitive, conceptual and historical development of belief functions. Three different interpretations (the marginally correct approximation, the qualitative model, and the quantitative model) of belief functions are investigated, and rough set theory and structured query language (SQL) are used to express belief function semantics. Section II presents applications of belief functions in information systems and auditing. Included are discussions on how a belief-function framework provides a more efficient and effective audit methodology and also the appropriateness of belief functions to represent uncertainties in audit evidence. The third section deals with applications of belief functions to mergers and acquisitions; financial analysis of engineering enterprises; forecast demand for mobile satellite services; modeling financial portfolios; and economics.
Author : Simon Parsons
Publisher : MIT Press
ISBN 13 : 9780262161688
Total Pages : 534 pages
Book Rating : 4.1/5 (616 download)
Download or read book Qualitative Methods for Reasoning Under Uncertainty written by Simon Parsons and published by MIT Press. This book was released on 2001 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using qualitative methods to deal with imperfect information.
Author : Didier J. Dubois
Publisher : Morgan Kaufmann
ISBN 13 : 1483282872
Total Pages : 379 pages
Book Rating : 4.4/5 (832 download)
Download or read book Uncertainty in Artificial Intelligence written by Didier J. Dubois and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence: Proceedings of the Eighth Conference (1992) covers the papers presented at the Eighth Conference on Uncertainty in Artificial Intelligence, held at Stanford University on July 17-19, 1992. The book focuses on the processes, methodologies, technologies, and approaches involved in artificial intelligence. The selection first offers information on Relative Evidential Support (RES), modal logics for qualitative possibility and beliefs, and optimizing causal orderings for generating DAGs from data. Discussions focus on reversal, swap, and unclique operators, modal representation of possibility, and beliefs and conditionals. The text then examines structural controllability and observability in influence diagrams, lattice-based graded logic, and dynamic network models for forecasting. The manuscript takes a look at reformulating inference problems through selective conditioning, entropy and belief networks, parallelizing probabilistic inference, and a symbolic approach to reasoning with linguistic quantifiers. The text also ponders on sidestepping the triangulation problem in Bayesian net computations; exploring localization in Bayesian networks for large expert systems; and expressing relational and temporal knowledge in visual probabilistic networks. The selection is a valuable reference for researchers interested in artificial intelligence.
Author : Zhan Deng
Publisher : Infinite Study
ISBN 13 :
Total Pages : 11 pages
Book Rating : 4./5 ( download)
Download or read book A novel decision probability transformation method based on belief interval written by Zhan Deng and published by Infinite Study. This book was released on with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Dempster–Shafer evidence theory, the basic probability assignment (BPA) can effectively represent and process uncertain information. How to transform the BPA of uncertain information into a decision probability remains a problem to be solved. In the light of this issue, we develop a novel decision probability transformation method to realize the transition from the belief decision to the probability decision in the framework of Dempster–Shafer evidence theory. The newly proposed method considers the transformation of BPA with multi-subset focal elements from the perspective of the belief interval, and applies the continuous interval argument ordered weighted average operator to quantify the data information contained in the belief interval for each singleton. Afterward, we present an approach to calculate the support degree of the singleton based on quantitative data information. According to the support degree of the singleton, the BPA of multi-subset focal elements is allocated reasonably. Furthermore, we introduce the concepts of probabilistic information content in this paper, which is utilized to evaluate the performance of the decision probability transformation method. Eventually, a few numerical examples and a practical application are given to demonstrate the rationality and accuracy of our proposed method.
Author : Rudolf Kruse
Publisher : Springer Science & Business Media
ISBN 13 : 3642767028
Total Pages : 495 pages
Book Rating : 4.6/5 (427 download)
Download or read book Uncertainty and Vagueness in Knowledge Based Systems written by Rudolf Kruse and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.
Author : Vo Van Toi
Publisher : Springer Science & Business Media
ISBN 13 : 3642120202
Total Pages : 339 pages
Book Rating : 4.6/5 (421 download)
Download or read book The Third International Conference on the Development of Biomedical Engineering in Vietnam written by Vo Van Toi and published by Springer Science & Business Media. This book was released on 2010-04-03 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vietnam is a rapidly developing, socially dynamic country, where interest in biomedical engineering activities has grown considerably in recent years. The leadership of the Vietnamese government, and of research and educational institutions, are well aware of the importance of this field for the development of the country and have instituted policies to promote its development. The political, economic and social environment within the country offers unique opportunities for the international community and this conference was intended to provide a vehicle for the sharing of experiences; development of support and collaboration networks for research; and exchange of ideas on how to improve the educational and entrepreneurial environment to better address the urgent needs of Vietnam. In January 2004, under the sponsorship of the U.S. National Science Foundation, a U.S. delegation that consisted of Biomedical Engineering professors from different universities in the United States, visited several universities and research institutions in Vietnam to assess the state of development of this field. This delegation proposed a five year plan that was enthusiastically embraced by the international scientific communities to actively develop collaborations with Vietnam. Within this framework, in July 2005, the First International Conference on the Development of Biomedical Engineering in Vietnam was held in Ho Chi Minh City. From that conference a Consortium of Vietnam-International Universities was created to advise and assist the development of Biomedical Engineering in Vietnamese universities.
Author : Thomas Augustin
Publisher : John Wiley & Sons
ISBN 13 : 1118763149
Total Pages : 448 pages
Book Rating : 4.1/5 (187 download)
Download or read book Introduction to Imprecise Probabilities written by Thomas Augustin and published by John Wiley & Sons. This book was released on 2014-04-11 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the theory has become widely accepted and has beenfurther developed, but a detailed introduction is needed in orderto make the material available and accessible to a wide audience.This will be the first book providing such an introduction,covering core theory and recent developments which can be appliedto many application areas. All authors of individual chapters areleading researchers on the specific topics, assuring high qualityand up-to-date contents. An Introduction to Imprecise Probabilities provides acomprehensive introduction to imprecise probabilities, includingtheory and applications reflecting the current state if the art.Each chapter is written by experts on the respective topics,including: Sets of desirable gambles; Coherent lower (conditional)previsions; Special cases and links to literature; Decision making;Graphical models; Classification; Reliability and risk assessment;Statistical inference; Structural judgments; Aspects ofimplementation (including elicitation and computation); Models infinance; Game-theoretic probability; Stochastic processes(including Markov chains); Engineering applications. Essential reading for researchers in academia, researchinstitutes and other organizations, as well as practitionersengaged in areas such as risk analysis and engineering.
Author : Daphne Koller
Publisher : MIT Press
ISBN 13 : 0262013193
Total Pages : 1268 pages
Book Rating : 4.2/5 (62 download)
Download or read book Probabilistic Graphical Models written by Daphne Koller and published by MIT Press. This book was released on 2009-07-31 with total page 1268 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions. Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Author : Thierry Denoeux
Publisher : Springer Science & Business Media
ISBN 13 : 3642294618
Total Pages : 442 pages
Book Rating : 4.6/5 (422 download)
Download or read book Belief Functions: Theory and Applications written by Thierry Denoeux and published by Springer Science & Business Media. This book was released on 2012-04-26 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Kari Sentz
Publisher :
ISBN 13 :
Total Pages : 100 pages
Book Rating : 4.3/5 (91 download)
Download or read book Combination of Evidence in Dempster-Shafer Theory written by Kari Sentz and published by . This book was released on 2002 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dempster-Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. Dempster-Shafer theory does not require an assumption regarding the probability of the individual constituents of the set or interval. This is a potentially valuable tool for the evaluation of risk and reliability in engineering applications when it is not possible to obtain a precise measurement from experiments, or when knowledge is obtained from expert elicitation. An important aspect of this theory is the combination of evidence obtained from multiple sources and the modeling of conflict between them. This report surveys a number of possible combination rules for Dempster-Shafer structures and provides examples of the implementation of these rules for discrete and interval-valued data.
