Info-gap Decision Theory Decisions Under Severe Uncertainty

Info-Gap Decision Theory presents 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. This idea is developed into a quantitative tool for decision-making under severe and unstructured uncertainty. An info-gap has two facets: pernicious uncertainty threatens failure, while propitious uncertainty entails the opportunity for windfall success. Info-gap theory has decision functions for defending against failure and for facilitating windfall, and explores the trade-off between them. The robustness function satisfices by guaranteeing survival while maximizing the immunity to uncertainty. In contrast, the opportunity function "windfalls" by reducing the immunity to sweeping success. These two strategies may be either mutually supporting or antagonistic. This book is essential for reliability analysis and strategic planning, and includes quantitative tools for decision support, risk assessment, option prioritizing, and trade-off analysis. Examples are presented from engineering analysis and design, project management, economic planning, financial risk assessment, biological conservation, medical decisions, homeland security and more. Theoretical discussions address value judgments, info-gap gambling, value of information, learning, conflict and consensus, robust-satisficing behavior and philosophical implications of info-gap uncertainty.Ben-Haim, Yakov is the author of 'Info-gap Decision Theory Decisions Under Severe Uncertainty', published 2006 under ISBN 9780123735522 and ISBN 0123735521.