Information-gap Decision Theory: Decisions Under Severe UncertaintyInformation-Gap Decision Theory presents a distinctive new theory of decision-making under severe uncertainty. Applications in engineering design and analysis, project management, economics, strategic planning, social decision making, environmental management, medical decisions, search and evasion problems, risk assessment, and other areas are discussed. Info-gap theory deals with many of the problems and questions of classical decision analysis such as risk assessment, gambling, value of information, trade-off analysis, and preference reversal, but the distinctive character of info-gap uncertainty repeatedly gives rise to new insights and unique decision algorithms. Furthermore, this book deals with many of the difficult interface issues facing the responsible decision maker such as value judgments concerning risk and immunity to failure, as well as philosophical implications of decision under uncertainty. This book is a fresh approach to the age-old problem of deciding responsibly with deficient information. An info-gap is the disparity between what is known and what needs to be known in order to make a well-founded decision. The book begins with a discussion of info-gap models of uncertainty, which provides an innovative approach to the quantification of severe lack of information. This book can be used in advanced undergraduate and graduate courses on decision theory and risk analysis. It is also of interest to practicing decision analysts and to researchers in decision theory and in human decision-making. |
Contents
Overview | 4 |
Uncertainty | 9 |
Robustness and Opportunity | 33 |
Copyright | |
11 other sections not shown
Other editions - View all
Info-gap Decision Theory: Decisions Under Severe Uncertainty Yakov Ben-Haim No preview available - 2006 |
Information Gap Decision Theory: Decisions Under Severe Uncertainty Yakov Ben-Haim No preview available - 2006 |
Common terms and phrases
ambient uncertainty analogy assessment calibration chapter choice choose coherence functions consider convex decision algorithm decision analyst decision maker decision problem decision vector decreases defined deflection demand value deviation discussion ellipsoid entails evidence example expressed formulate Fourier gap function greater immunity functions immunity to uncertainty implies increases increment info-gap decision theory info-gap inference info-gap model info-gap uncertainty investment level of uncertainty lottery matrix maximizes model of uncertainty nominal duration opportunity function optimal action option path positive definite matrix preferences probabilistic probability problem q,rc qw(rw relation represented reward function risk aversion risk sensitivity robust-optimal action robustness and opportunity robustness curve robustness function robustness premium satisficing strategy structure tainty task theorem tion trade-off u₁ uncer uncertainty model uncertainty parameter uncertainty weight update upper coherence function variable vector q warrant windfall cost windfall gain windfall reward