Download or read book Uncertainty and Information written by George J. Klir and published by John Wiley & Sons. This book was released on 2005-11-22 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deal with information and uncertainty properly and efficientlyusing tools emerging from generalized information theory Uncertainty and Information: Foundations of Generalized InformationTheory contains comprehensive and up-to-date coverage of resultsthat have emerged from a research program begun by the author inthe early 1990s under the name "generalized information theory"(GIT). This ongoing research program aims to develop a formalmathematical treatment of the interrelated concepts of uncertaintyand information in all their varieties. In GIT, as in classicalinformation theory, uncertainty (predictive, retrodictive,diagnostic, prescriptive, and the like) is viewed as amanifestation of information deficiency, while information isviewed as anything capable of reducing the uncertainty. A broadconceptual framework for GIT is obtained by expanding theformalized language of classical set theory to include moreexpressive formalized languages based on fuzzy sets of varioustypes, and by expanding classical theory of additive measures toinclude more expressive non-additive measures of varioustypes. This landmark book examines each of several theories for dealingwith particular types of uncertainty at the following fourlevels: * Mathematical formalization of the conceived type ofuncertainty * Calculus for manipulating this particular type ofuncertainty * Justifiable ways of measuring the amount of uncertainty in anysituation formalizable in the theory * Methodological aspects of the theory With extensive use of examples and illustrations to clarify complexmaterial and demonstrate practical applications, generoushistorical and bibliographical notes, end-of-chapter exercises totest readers' newfound knowledge, glossaries, and an Instructor'sManual, this is an excellent graduate-level textbook, as well as anoutstanding reference for researchers and practitioners who dealwith the various problems involving uncertainty and information. AnInstructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Download or read book The Analytics of Uncertainty and Information written by Sushil Bikhchandani and published by Cambridge University Press. This book was released on 2013-08-12 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: There has been explosive progress in the economic theory of uncertainty and information in the past few decades. This subject is now taught not only in departments of economics but also in professional schools and programs oriented toward business, government and administration, and public policy. This book attempts to unify the subject matter in a simple, accessible manner. Part I of the book focuses on the economics of uncertainty; Part II examines the economics of information. This revised and updated second edition places a greater focus on game theory. New topics include posted-price markets, mechanism design, common-value auctions, and the one-shot deviation principle for repeated games.

Download or read book Economie de L incertain Et de L information written by Jean-Jacques Laffont and published by MIT Press. This book was released on 1989 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Economics of Uncertainty and Information may be used in conjunction with Loffont's Fundamentals of Economics in an advanced course in microeconomics.

Download or read book Uncertainty Based Information written by George J. Klir and published by Physica. This book was released on 2013-06-05 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Uncertainty Information Management and Disclosure Decisions written by Tamara Afifi and published by Routledge. This book was released on 2015-12-22 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume integrates scholarly work on disclosure and uncertainty with the most up-to-date, cutting edge research, theories, and applications. Uncertainty is an ever-present part of human relationships, and the ways in which people reduce and/or manage uncertainty involves regulating their communication with others through revealing and concealing information. This collection is devoted to collating knowledge in these areas, advancing theory and presenting work that is socially meaningful. This work includes contributions from renowned scholars in interpersonal uncertainty and information regulation, focusing on processes that bridge boundaries within and across disciplines, while maintaining emphasis on interpersonal contexts. Disciplines represented here include interpersonal, family, and health communication, as well as relational and social psychology. Key features of the volume include: comprehensive coverage integrating the latest research on disclosure, information seeking, and uncertainty a highly theoretical content, socially meaningful in nature (applied to real-world contexts) an interdisciplinary approach that crosses sub-fields within communication. This volume is a unique and timely resource for advanced study in interpersonal, health, or family communication. With its emphasis on theory, the book is an excellent resource for graduate courses addressing theory and/or theory construction, and it will also appeal to scholars interested in applied research.

Download or read book Uncertainty Management in Information Systems written by Amihai Motro and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: As its title suggests, "Uncertainty Management in Information Systems" is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, "From Needs to Solutions," indicates, this book presents view points of information systems experts on the needs that challenge the uncer tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer. This book was released on 2007-09-14 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Uncertainty in Geographical Information written by Jingxiong Zhang and published by CRC Press. This book was released on 2002-03-29 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: As Geographic Information Systems (GIS) have developed and their applications have been extended, the issue of uncertainty has become increasingly recognized. It is highlighted by the need to demystify the inherently complex geographical world to facilitate computerization in GIS, by the inaccuracies that emerge from man-machine interactions in dat

Download or read book Design Decisions Under Uncertainty with Limited Information written by Efstratios Nikolaidis and published by CRC Press. This book was released on 2017-06-16 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today's business environment involves design decisions with significant uncertainty. To succeed, decision-makers should replace deterministic methods with a risk-based approach that accounts for the decision maker¿s risk tolerance. In many problems, it is impractical to collect data because rare or one-time events are involved. Therefore, we need a methodology to model uncertainty and make choices when we have limited information. This methodology must use all available information and rely only on assumptions that are supported by evidence. This book explains theories and tools to represent uncertainty using both data and expert judgment. It teaches the reader how to make design or business decisions when there is limited information with these tools. Readers will learn a structured, risk-based approach, which is based on common sense principles, for design and business decisions. These decisions are consistent with the decision-maker¿s risk attitude. The book is exceptionally suited as educational material because it uses everyday language and real-life examples to elucidate concepts. It demonstrates how these concepts touch our lives through many practical examples, questions and exercises. These are designed to help students learn that first they should understand a problem and then establish a strategy for solving it, instead of using trial-and-error approaches. This volume is intended for undergraduate and graduate courses in mechanical, civil, industrial, aerospace, and ocean engineering and for researchers and professionals in these disciplines. It will also benefit managers and students in business administration who want to make good decisions with limited information.

Download or read book Uncertainty in Economics written by Peter Diamond and published by Academic Press. This book was released on 2014-05-10 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Economics: Readings and Exercises provides information pertinent to the fundamental aspects of the economics of uncertainty. This book discusses ho uncertainty affects both individual behavior and standard equilibrium theory. Organized into three parts encompassing 30 chapters, this book begins with an overview of the relevance of expected utility maximization for positive and normative theories of individual choice. This text then examines the biases in judgments, which reveal some heuristics of thinking under uncertainty. Other chapters consider the effect of restricting trade in contingent commodities to those trades that can be affected through the stock and bond markets. This book discusses as well the individual problem of sequential choice and equilibria, which are built around the notion of sequential choice. The final chapter deals with an entirely different aspect of the economics of information and reverts to the assumption that markets are perfect and costless. This book is a valuable resource for economists and students.

Download or read book Fuzzy Sets Uncertainty And Information written by Klir and published by . This book was released on 1995 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Theory of Decision Under Uncertainty written by Itzhak Gilboa and published by Cambridge University Press. This book was released on 2009-03-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions - first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer Science & Business Media. This book was released on 2011-11-07 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Download or read book Uncertainty Quantification and Predictive Computational Science written by Ryan G. McClarren and published by Springer. This book was released on 2018-11-23 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.

Download or read book An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems written by Luis Tenorio and published by SIAM. This book was released on 2017-07-06 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inverse problems are found in many applications, such as medical imaging, engineering, astronomy, and geophysics, among others. To solve an inverse problem is to recover an object from noisy, usually indirect observations. Solutions to inverse problems are subject to many potential sources of error introduced by approximate mathematical models, regularization methods, numerical approximations for efficient computations, noisy data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution. Such assessment is interdisciplinary by nature, as it requires, in addition to knowledge of the particular application, methods from applied mathematics, probability, and statistics. This book bridges applied mathematics and statistics by providing a basic introduction to probability and statistics for uncertainty quantification in the context of inverse problems, as well as an introduction to statistical regularization of inverse problems. The author covers basic statistical inference, introduces the framework of ill-posed inverse problems, and explains statistical questions that arise in their applications. An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems?includes many examples that explain techniques which are useful to address general problems arising in uncertainty quantification, Bayesian and non-Bayesian statistical methods and discussions of their complementary roles, and analysis of a real data set to illustrate the methodology covered throughout the book.

Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems Theory and Foundations written by Jesús Medina and published by Springer. This book was released on 2018-05-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

Download or read book Taming Uncertainty written by Ralph Hertwig and published by MIT Press. This book was released on 2019-08-13 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: An examination of the cognitive tools that the mind uses to grapple with uncertainty in the real world. How do humans navigate uncertainty, continuously making near-effortless decisions and predictions even under conditions of imperfect knowledge, high complexity, and extreme time pressure? Taming Uncertainty argues that the human mind has developed tools to grapple with uncertainty. Unlike much previous scholarship in psychology and economics, this approach is rooted in what is known about what real minds can do. Rather than reducing the human response to uncertainty to an act of juggling probabilities, the authors propose that the human cognitive system has specific tools for dealing with different forms of uncertainty. They identify three types of tools: simple heuristics, tools for information search, and tools for harnessing the wisdom of others. This set of strategies for making predictions, inferences, and decisions constitute the mind's adaptive toolbox. The authors show how these three dimensions of human decision making are integrated and they argue that the toolbox, its cognitive foundation, and the environment are in constant flux and subject to developmental change. They demonstrate that each cognitive tool can be analyzed through the concept of ecological rationality—that is, the fit between specific tools and specific environments. Chapters deal with such specific instances of decision making as food choice architecture, intertemporal choice, financial uncertainty, pedestrian navigation, and adolescent behavior.