Info-Gap Decision Theory: Decisions Under Severe Uncertainty

Author:   Yakov Ben-Haim (Technion - Israel Institute of Technology, Haifa, Israel.)
Publisher:   Elsevier Science Publishing Co Inc
Edition:   2nd edition
ISBN:  

9780123735522


Pages:   384
Publication Date:   07 August 2006
Format:   Hardback
Availability:   Out of print, replaced by POD   Availability explained
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Info-Gap Decision Theory: Decisions Under Severe Uncertainty


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Overview

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.

Full Product Details

Author:   Yakov Ben-Haim (Technion - Israel Institute of Technology, Haifa, Israel.)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Edition:   2nd edition
Dimensions:   Width: 16.50cm , Height: 2.00cm , Length: 24.00cm
Weight:   0.820kg
ISBN:  

9780123735522


ISBN 10:   0123735521
Pages:   384
Publication Date:   07 August 2006
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

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

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Author Information

Yakov Ben-Haim originated info-gap theory which has been applied to decision-making in engineering, biological conservation, behavioral science, medicine, economic policy, project management and homeland security. Dr. Ben-Haim is a professor in Mechanical Engineering at the Technion - Israel Institute of Technology, and holds the Yitzhak Moda'i Chair in Technology and Economics. He has been a visiting professor in Canada, Europe, Japan, Korea and the U.S.

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