By
Yakov Ben-Haim, Technion - Israel Institute of Technology, Haifa, Israel.
Description
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. This book 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.
Audience:
Info-Gap Decision Theory is directed at decision analysts, which includes design engineers, safety analysts, project managers, biological
conservation planners, industrial and manufacturing managers, economic analysts, medical diagnosis and informatics experts, social and
governmental planners, and all others engaged in quantitative model-based decision-support activities.
