Info-Gap Decision Theory: Decisions Under Severe UncertaintyElsevier, 11/10/2006 - 384 من الصفحات Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. Info-Gap Decision Theory is written for decision analysts. The term "decision analyst" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts, usually without calling themselves by this name. In addition to engineers, decision analysts work in planning offices for public agencies, in project management consultancies, they are engaged in manufacturing process planning and control, in financial planning and economic analysis, in decision support for medical or technological diagnosis, and so on and on. Decision analysts provide quantitative support for the decision-making process in all areas where systematic decisions are made. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas - especially biological conservation, economic policy formulation, preparedness against terrorism, and medical decision-making. Pertinent new examples have been included. Second, the combination of info-gap analysis with probabilistic decision algorithms has found wide application. Consequently "hybrid" models of uncertainty, which were treated exclusively in a separate chapter in the previous edition, now appear throughout the book as well as in a separate chapter. Finally, info-gap explanations of robust-satisficing behavior, and especially the Ellsberg and Allais "paradoxes", are discussed in a new chapter together with a theorem indicating when robust-satisficing will have greater probability of success than direct optimizing with uncertain models.
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... for fuller answers, and even for new questions, is still at full steam. The reader is invited to join the search. Yakov Ben-Haim The Technion Haifa, Israel June 2001 This second edition entails changes of several sorts. First, info-gap xii.
Decisions Under Severe Uncertainty Yakov Ben-Haim. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas — especially biological conservation, economic policy formulation ...
... entail no measure functions: neither probability densities nor fuzzy membership functions.2 Info-gap models concentrate on the disparity between what is known and what could be known, while making very little commitment about the ...
... entailing the threat of failure, or propitious, entailing the possibility of unimagined success. Info-gap theory addresses these two conflicting potentials with two immunity functions. The robustness function assesses the immunity to ...
... entail continuous variation of the horizon of uncertainty α. However, in some situations the uncertainty is discrete. For instance, ordinal preferences among several options can be specified by positive integers, where a low integer ...
المحتوى
1 | |
9 | |
37 | |
4 Value Judgments | 115 |
5 Antagonistic and Sympathetic Immunities | 129 |
6 Gambling and Risk Sensitivity | 149 |
7 Value of Information | 185 |
8 Learning | 207 |
10 Hybrid Uncertainties | 249 |
11 RobustSatisficing Behavior | 267 |
Risk Assessment in Project Management | 297 |
13 Implications of InfoGap Uncertainty | 317 |
References | 347 |
Author Index | 357 |
Subject Index | 361 |
9 Coherent Uncertainties and Consensus | 231 |