Possibility Theory
Possibility Theory

Author: Didier Dubois

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 274

ISBN-13: 1468452878

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In the evolution of scientific theories, concern with uncertainty is almost invariably a concomitant of maturation. This is certainly true of the evolution· of physics, economics, operations research, communication sciences, and a host of other fields. And it is true of what has been happening more recently in the area of artificial intelligence, most notably in the development of theories relating to the management of uncertainty in knowledge-based systems. In science, it is traditional to deal with uncertainty through the use of probability theory. In recent years, however, it has become increasingly clear that there are some important facets of uncertainty which do not lend themselves to analysis by classical probability-based methods. One such facet is that of lexical elasticity, which relates to the fuzziness of words in natural languages. As a case in point, even a simple relation X, Y, and Z, expressed as if X is small and Y is very large then between Z is not very small, does not lend itself to a simple interpretation within the framework of probability theory by reason of the lexical elasticity of the predicates small and large.

Possibility Theory for the Design of Information Fusion Systems
Possibility Theory for the Design of Information Fusion Systems

Author: Basel Solaiman

Publisher: Springer Nature

Published: 2019-12-26

Total Pages: 294

ISBN-13: 3030328538

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This practical guidebook describes the basic concepts, the mathematical developments, and the engineering methodologies for exploiting possibility theory for the computer-based design of an information fusion system where the goal is decision support for industries in smart ICT (information and communications technologies). This exploitation of possibility theory improves upon probability theory, complements Dempster-Shafer theory, and fills an important gap in this era of Big Data and Internet of Things. The book discusses fundamental possibilistic concepts: distribution, necessity measure, possibility measure, joint distribution, conditioning, distances, similarity measures, possibilistic decisions, fuzzy sets, fuzzy measures and integrals, and finally, the interrelated theories of uncertainty..uncertainty. These topics form an essential tour of the mathematical tools needed for the latter chapters of the book. These chapters present applications related to decision-making and pattern recognition schemes, and finally, a concluding chapter on the use of possibility theory in the overall challenging design of an information fusion system. This book will appeal to researchers and professionals in the field of information fusion and analytics, information and knowledge processing, smart ICT, and decision support systems.

Probability
Probability

Author: Rick Durrett

Publisher: Cambridge University Press

Published: 2010-08-30

Total Pages:

ISBN-13: 113949113X

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This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject.

Possibility Theory and the Risk
Possibility Theory and the Risk

Author: Irina Georgescu

Publisher: Springer

Published: 2012-01-12

Total Pages: 130

ISBN-13: 3642247407

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The book deals with some of the fundamental issues of risk assessment in grid computing environments. The book describes the development of a hybrid probabilistic and possibilistic model for assessing the success of a computing task in a grid environment

Advances in Fuzzy Sets, Possibility Theory, and Applications
Advances in Fuzzy Sets, Possibility Theory, and Applications

Author: P.P. Wang

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 421

ISBN-13: 1461337542

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Since its inception by Professor Lotfi Zadeh about 18 years ago, the theory of fuzzy sets has evolved in many directions, and is finding applications in a wide variety of fields in which the phenomena under study are too complex or too ill-defined to be analyzed by conventional techniques. Thus, by providing a basis for a systematic approach to approximate reasoning and inexact inference, the theory of fuzzy sets may well have a substantial impact on scientific methodology in the years ahead, particularly in the realms of psychology, economics, engineering, law, medicine, decision-analysis, information retrieval, and artificial intelli gence. This volume consists of 24 selected papers invited by the editor, Professor Paul P. Wang. These papers cover the theory and applications of fuzzy sets, almost equal in number. We are very fortunate to have Professor A. Kaufmann to contribute an overview paper of the advances in fuzzy sets. One special feature of this volume is the strong participation of Chinese researchers in this area. The fact is that Chinese mathematicians, scientists and engineers have made important contributions to the theory and applications of fuzzy sets through the past decade. However, not until the visit of Professor A. Kaufmann to China in 1974 and again in 1980, did the Western World become fully aware of the important work of Chinese researchers. Now, Professor Paul Wang has initiated the effort to document these important contributions in this volume to expose them to the western researchers.

A Combinatorial Theory of Possibility
A Combinatorial Theory of Possibility

Author: D. M. Armstrong

Publisher: Cambridge University Press

Published: 1989-09-29

Total Pages: 174

ISBN-13: 9780521377805

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Preface Part I. Non-Naturalist Theories of Possibility: 1. Causal argument 2. Non-Naturalist theories of possibility Part II. A Combinatorial and Naturalist Account of Possibility: 3. Possibility in a simple world 4. Expanding and contracting the world 5. Relative atoms 6. Are there de re incompatibilities and necessities? 7. Higher-order entities, negation and causation 8. Supervenience 9. Mathematics 10. Final questions: logic Works cited Appendix: Tractarian Nominalism Brian Skyrms Index.

Introduction to Probability Models
Introduction to Probability Models

Author: Sheldon M. Ross

Publisher: Academic Press

Published: 2006-12-11

Total Pages: 801

ISBN-13: 0123756871

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Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes. There are two approaches to the study of probability theory. One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text. The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students. This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes. New to this Edition: - 65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains - Contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams - Updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bank - Includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field Hallmark features: - Superior writing style - Excellent exercises and examples covering the wide breadth of coverage of probability topics - Real-world applications in engineering, science, business and economics

Probability Theory
Probability Theory

Author: IntroBooks

Publisher: IntroBooks

Published: 2018-02-21

Total Pages: 33

ISBN-13:

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Events are a kind of abstraction achieved through mathematical process. This abstraction is done on the base of non-deterministic events. Measured quantities can also be used for such abstraction. Measured quantities can be single occurrence or also follow random fashion for time evolving multiple occurrences. Making predictions about the outcome of random events is not always easy or even impossible sometimes. However, if influences are made on sequence of individual events, they will tend to follow certain patterns that are much easy to study, practice and predict. For instance, if outcome of coin flipping or roll of dice is influenced by outer factors such as friction, they will follow a specific pattern when proving outcome. Once this certain pattern is figured out and understood properly, it becomes much easier to predict the outcome with maximum accuracy. It means that it is hard to understand future outcome of subsequent random events that makes it hard to predict them. However, it is easy to predict pattern exhibited by these group of events that makes it easy to predict them and their corresponding events also. To describe such patterns certain mathematical results or concepts are used. Law of large numbers and central limit theorem are two main concepts that are used to study and describe such patterns followed by sequential random events.

Uncertainty Theory
Uncertainty Theory

Author: Baoding Liu

Publisher: Springer

Published: 2007-09-14

Total Pages: 263

ISBN-13: 3540731652

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This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. For this new edition the entire text has been totally rewritten. The chapters on chance theory and uncertainty theory are completely new. Mathematicians, researchers, engineers, designers, and students will find this work a stimulating and useful reference.