Info-Gap Decision Theory by Ben-Haim, Yakov;

Decisions Under Severe Uncertainty

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A termék adatai:

Kiadás sorszáma 2
Kiadó Academic Press
Megjelenés dátuma 2006. augusztus 7.

ISBN 9780123735522
Kötéstípus Keménykötés
Terjedelem384 oldal
Méret 240x165 mm
Súly 820 g
Nyelv angol

Kategóriák

Építőmérnöki tudományok, építőipar A számítástudomány matematikai elmélete Menedzsment, vállalatirányítás További könyvek a gazdaság területén További könyvek a számítástechnika területén

Hosszú leírás:

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.

New theory developed systematically
Many examples from diverse disciplines
Realistic representation of severe uncertainty
Multi-faceted approach to risk
Quantitative model-based decision theory

Több

Tartalomjegyzék:

1. Overview
2. Uncertainty
3. Robustness and Opportuneness
4. Value Judgments
5. Antagonistic and Sympathetic Immunities
6. Gambling and Risk Sensitivity
7. Value of Information
8. Learning
9. Coherent Uncertainties and Consensus
10. Hybrid Uncertainties
11. Robust-Satisficing Behavior
12. Retrospective Essay: Risk Assessment in Project Management
13. Implications of Info-Gap Uncertainty