Author: Roger M. Cooke
Publisher: Oxford University Press
ISBN: 0195362373
Category : Science
Languages : en
Pages : 334
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Book Description
This book is an extensive survey and critical examination of the literature on the use of expert opinion in scientific inquiry and policy making. The elicitation, representation, and use of expert opinion is increasingly important for two reasons: advancing technology leads to more and more complex decision problems, and technologists are turning in greater numbers to "expert systems" and other similar artifacts of artificial intelligence. Cooke here considers how expert opinion is being used today, how an expert's uncertainty is or should be represented, how people do or should reason with uncertainty, how the quality and usefulness of expert opinion can be assessed, and how the views of several experts might be combined. He argues for the importance of developing practical models with a transparent mathematic foundation for the use of expert opinion in science, and presents three tested models, termed "classical," "Bayesian," and "psychological scaling." Detailed case studies illustrate how they can be applied to a diversity of real problems in engineering and planning.
Author: Roger Cooke
Publisher:
ISBN: 9780197730379
Category : Decision making
Languages : en
Pages : 0
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Book Description
This volume contains an extensive survey and critical examination of current views on the use of expert opinion in scientific inquiry and policy-making.
Author: Bilal M. Ayyub
Publisher: CRC Press
ISBN: 9780849310874
Category : Technology & Engineering
Languages : en
Pages : 328
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Book Description
Experts, despite their importance and value, can be double-edged swords. They can make valuable contributions from their deep base of knowledge, but those contributions may also contain their own biases and pet theories. Therefore, selecting experts, eliciting their opinions, and aggregating their opinions must be performed and handled carefully, with full recognition of the uncertainties inherent in those opinions. Elicitation of Expert Opinions for Uncertainty and Risks illuminates those uncertainties and builds a foundation of philosophy, background, methods, and guidelines that helps its readers effectively execute the elicitation process. Based on the first-hand experiences of the author, the book is filled with illustrations, examples, case studies, and applications that demonstrate not only the methods and successes of expert opinion elicitation, but also its pitfalls and failures. Studies show that in the future, analysts, engineers, and scientists will need to solve ever more complex problems and reach decisions with limited resources. This will lead to an increased reliance on the proper treatment of uncertainty and on the use of expert opinions. Elicitation of Expert Opinions for Uncertainty and Risks will help prepare you to better understand knowledge and ignorance, to successfully elicit expert opinions, to select appropriate expressions of those opinions, and to use various methods to model and aggregate opinions.
Author: Anthony O'Hagan
Publisher: John Wiley & Sons
ISBN: 0470033304
Category : Mathematics
Languages : en
Pages : 338
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Book Description
Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples. This is achieved by: Presenting a methodological framework for the elicitation of expert knowledge incorporating findings from both statistical and psychological research. Detailing techniques for the elicitation of a wide range of standard distributions, appropriate to the most common types of quantities. Providing a comprehensive review of the available literature and pointing to the best practice methods and future research needs. Using examples from many disciplines, including statistics, psychology, engineering and health sciences. Including an extensive glossary of statistical and psychological terms. An ideal source and guide for statisticians and psychologists with interests in expert judgement or practical applications of Bayesian analysis, Uncertain Judgements will also benefit decision-makers, risk analysts, engineers and researchers in the medical and social sciences.
Author: Jerzy W. Grzymala-Busse
Publisher: Springer Science & Business Media
ISBN: 146153982X
Category : Computers
Languages : en
Pages : 242
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Book Description
3. Textbook for a course in expert systems,if an emphasis is placed on Chapters 1 to 3 and on a selection of material from Chapters 4 to 7. There is also the option of using an additional commercially available sheU for a programming project. In assigning a programming project, the instructor may use any part of a great variety of books covering many subjects, such as car repair. Instructions for mostofthe "weekend mechanic" books are close stylisticaUy to expert system rules. Contents Chapter 1 gives an introduction to the subject matter; it briefly presents basic concepts, history, and some perspectives ofexpert systems. Then itpresents the architecture of an expert system and explains the stages of building an expert system. The concept of uncertainty in expert systems and the necessity of deal ing with the phenomenon are then presented. The chapter ends with the descrip tion of taxonomy ofexpert systems. Chapter 2 focuses on knowledge representation. Four basic ways to repre sent knowledge in expert systems are presented: first-order logic, production sys tems, semantic nets, and frames. Chapter 3 contains material about knowledge acquisition. Among machine learning techniques, a methodofrule learning from examples is explained in de tail. Then problems ofrule-base verification are discussed. In particular, both consistency and completeness oftherule base are presented.
Author: Millett Granger Morgan
Publisher: Cambridge University Press
ISBN: 113993581X
Category : Psychology
Languages : en
Pages : 376
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Book Description
The authors explain the ways in which uncertainty is an important factor in the problems of risk and policy analysis. This book outlines the source and nature of uncertainty, discusses techniques for obtaining and using expert judgment, and reviews a variety of simple and advanced methods for analyzing uncertainty.
Author: Kostas Kampourakis
Publisher: Oxford University Press, USA
ISBN: 0190871660
Category : Philosophy
Languages : en
Pages : 273
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Book Description
Anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings by referring to the uncertainties in these areas of research. Uncertainty: How It Makes Science Advance shows that uncertainty is an inherent feature of science that makes it advance by motivating further research.
Author: Bilal M. Ayyub
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages :
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Book Description
Author: S.O. Funtowicz
Publisher: Springer Science & Business Media
ISBN: 9400906218
Category : Social Science
Languages : en
Pages : 254
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Book Description
This book explains the notational system NUSAP (Numeral, Unit, Spread, Assessment, Pedigree) and applies it to several examples from the environmental sciences. The authors are now making further extensions of NUSAP, including an algorithm for the propagation of quality-grades through models used in risk and safety studies. They are also developing the concept of `Post-normal Science', in which quality assurance of information requires the participation of `extended peer-communities' lying outside the traditional expertise.
Author: William Briggs
Publisher: Springer
ISBN: 3319397567
Category : Mathematics
Languages : en
Pages : 274
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Book Description
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance." The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.