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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... failure and windfall success. Uncertainty may be either pernicious, entailing the threat of failure, or propitious, entailing the possibility of unimagined success. Info-gap theory addresses these two conflicting potentials with two ...
... failure as expressed by the robustness of the decision. However, excessive concentration on failure prevention can lead to lethargic behavior and to the loss of promising opportunities. An important question is whether or not robustness ...
... failure to success. In chapter 7 we quantify the value of information based on the info-gap robustness function. Again we are treading on terrain already covered by powerful probabilistic theories, as in the study of gambling. Again we ...
... , off-shore ship-mooring systems, dynamics of nuclear particle accelerators, aerodynamic flutter and instability as demonstrated by the dramatic failure of the Tacoma Narrows bridge, orbital and attitude Chapter 2. Uncertainty 27.
Decisions Under Severe Uncertainty Yakov Ben-Haim. dramatic failure of the Tacoma Narrows bridge, orbital and attitude instabilities encountered in the control of spacecraft, as well as many other examples [119, 168, 169]. We now move ...
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 |