Uncertainty

The US government spends billions of dollars every year to reduce uncertainty: to monitor and forecast everything from the weather to the spread of disease. In other words, we spend a lot of money to

Uncertainty is a fundamental and unavoidable feature of daily life; in order to dealwith uncertaintly intelligently, we need to be able to represent it and reason about it. In thisbook, Joseph Halpern

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

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

The Value of Uncertainty begins by tracing the growth in the equity derivative markets prior to the events of September 2008, and demonstrates how exotic derivatives formed a significant component of

?Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes

Uncertainty pervades the big decisions we all make in our lives. How much should we pay into our pensions each month? Should we take regular exercise? Expand the business? Change our strategy? Enter a

Praise for the First Edition". . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner." —Mathematical GeosciencesThe state of the

Rational and reassuring, Uncertainty in Medicine forges a new path for approaching medical uncertainty by arming readers from an array of disciplines with the tools they need to diagnose, treat, and c

In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers var

The purpose of this book is to help readers understand the impact of uncertainty on learning processes. It is the first comprehensive book on the subject of learning with uncertainty and covers the ma

The book provides a short review of the classical approach to planning and decision making under uncertainty. It further explains the concept of state-contingent goods, and it extends earlier work on

This volume draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Malaga, Spain, organized by the University of Malaga. The conferenc

This book tries to sort out the different meanings of uncertainty and to discover their foundations. It shows that uncertainty can be represented using various tools and mental guidelines. Coverage al

Using formal systems to represent and reason about uncertainty.

Like the De Groot winning first edition, the second edition of Principles of Uncertainty is an accessible, comprehensive guide to the theory of Bayesian Statistics written in an appealing, inviting st

At the core of both art and science we find the twin forces of probability and uncertainty. However, these two worlds have been tenuously entangled for decades. On the one hand, artists continue to as

A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using rea

Uncertainty in Policy Making explores how uncertainty is interpreted and used by policy makers, experts and politicians. It argues that conventional notions of rational, evidence-based policy making -

In his first collection of short stories, rob mclennans The Uncertainty Principle uses not a single wasted word to explore history, contemporary culture, human relationships, and the ways in which we

Science is a quest for certainty, but lack of certainty is the driving force behind all of its endeavors. This book, specifically, examines the uncertainty of technological and industrial science. Unc

A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.

In life, uncertainty surrounds us. Things that we thought were good for us turn outto be bad for us (and vice versa); people we thought we knew well behave in mysterious ways; thestock market takes a

The relationship between the price of oil and the level of economic activity is a fundamental issue in macroeconomics. There is an ongoing debate in the literature about whether positive oil price sho

Mark Kraushaar's collection; winner of the Anthony Hecht Poetry Prize 2010.

The US government spends billions of dollars every year to reduce uncertainty: to monitor and forecast everything from the weather to the spread of disease. In other words, we spend a lot of money to

This book constitutes the refereed proceedings of the 4th International Conference on Scalable Uncertainty Management, SUM 2010, held in Toulouse, France, in September 2010. The 26 revised full papers

Support for addressing the on-going global changes needs solutions for new scientific problems which in turn require new concepts and tools. A key issue concerns a vast variety of irreducible uncertai

Examining how youths in fourteen industrialized societies make the transition to adulthood in an era of globalization and rising uncertainty, this collection of essays investigates the impact that ins

Dealing effectively with uncertainty requires today's project manager to be familiar with a broad spectrum of strategies, encompassing both 'hard' and 'soft' methods. This theme of unified thinking (i

Observations of uncertainty in measured data with time improves forecasting capability in a wide range of fields in engineering. This book provides an introduction to uncertainty forecasting based on

This 2003 book represents an exciting intellectual meeting of researchers from diverse subfields to analyze how and why uncertainty affects American politics. It seeks to reconnect research traditions that have seldom spoken to one another. Though used by formal theorists, empiricists, and historians in a parallel fashion for a number of years, the notion of uncertainty has often been introduced only to explain away anomalies, provide backing for a larger argument, or justify a particular methodology. Uncertainty has rarely been considered in its own right or as a concept that might connect researchers from different subfields. The authors demonstrate some of the many substantive effects that uncertainty has on the bureaucracy, voters, and elected officials. They also reveal the origins and consequences of uncertainty to remind researchers across the discipline how central the idea should be to any serious study of US politics.

This 2003 book represents an exciting intellectual meeting of researchers from diverse subfields to analyze how and why uncertainty affects American politics. It seeks to reconnect research traditions that have seldom spoken to one another. Though used by formal theorists, empiricists, and historians in a parallel fashion for a number of years, the notion of uncertainty has often been introduced only to explain away anomalies, provide backing for a larger argument, or justify a particular methodology. Uncertainty has rarely been considered in its own right or as a concept that might connect researchers from different subfields. The authors demonstrate some of the many substantive effects that uncertainty has on the bureaucracy, voters, and elected officials. They also reveal the origins and consequences of uncertainty to remind researchers across the discipline how central the idea should be to any serious study of US politics.

The Economics of Uncertainty and Information may be used in conjunction with Loffont's Fundamentals of Economics in an advanced course in microeconomics. Both texts provide a thorough account of moder

How cutting-edge economics can improve decision-making methods for doctorsAlthough uncertainty is a common element of patient care, it has largely been overlooked in research on evidence-based medicin

Born of a belief that economic insights should not require much mathematical sophistication, this book proposes novel and parsimonious methods to incorporate ignorance and uncertainty into economic modeling, without complex mathematics. Economics has made great strides over the past several decades in modeling agents' decisions when they are incompletely informed, but many economists believe that there are aspects of these models that are less than satisfactory. Among the concerns are that ignorance is not captured well in most models, that agents' presumed cognitive ability is implausible, and that derived optimal behavior is sometimes driven by the fine details of the model rather than the underlying economics. Compte and Postlewaite lay out a tractable way to address these concerns, and to incorporate plausible limitations on agents' sophistication. A central aspect of the proposed methodology is to restrict the strategies assumed available to agents.

Born of a belief that economic insights should not require much mathematical sophistication, this book proposes novel and parsimonious methods to incorporate ignorance and uncertainty into economic modeling, without complex mathematics. Economics has made great strides over the past several decades in modeling agents' decisions when they are incompletely informed, but many economists believe that there are aspects of these models that are less than satisfactory. Among the concerns are that ignorance is not captured well in most models, that agents' presumed cognitive ability is implausible, and that derived optimal behavior is sometimes driven by the fine details of the model rather than the underlying economics. Compte and Postlewaite lay out a tractable way to address these concerns, and to incorporate plausible limitations on agents' sophistication. A central aspect of the proposed methodology is to restrict the strategies assumed available to agents.

The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The autho