Background
Ben-Haim, Yakov was born on October 7, 1952 in Chicago, Illinois, United States. Son of John Paul and Muriel Moulton.
(Everyone makes decisions, but not everyone is a decision ...)
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. * New theory developed systematically. * Many examples from diverse disciplines. * Realistic representation of severe uncertainty. * Multi-faceted approach to risk. * Quantitative model-based decision theory.
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(The aim of the book is to develop methodology for reliabl...)
The aim of the book is to develop methodology for reliablity analysis which is particularly suited to the types of partial information characteristic of mechanical systems and structures. The book is designed as an upper-level undergraduate or first-year graduate text on robust reliability of mechanical systems. It will give the student or engineer a working knowledge of robust reliability which will enable him to analyse the reliability of mechanical systems. Each chapter is introduced with a brief conceptual survey of the main ideas, which are then developed through examples. Problems at the end of each chapter give the student the opportunity to strengthen and extend his or her understanding.
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(Uncertainty influences the individual as well as society....)
Uncertainty influences the individual as well as society. Because of this it is important to enhance our understanding of uncertainty. Firstly, is there a unique definition of uncertainty in the natural and technological worlds? Secondly, how can we model uncertainty? Is it purely a state of mind, the lack of complete knowledge, or is it a phenomenon in its own right? What heuristic and mathematical models are available? What types of questions about uncertainty can be formulated? What questions can be realistically answered? Do scholars in diverse fields agree on these issues? These and other questions are addressed by scholars from mechanical, civil, electrical, material, aerospace and ocean engineering, from applied mathematics, economics, industrial engineering and operations research, control theory, geodesy, systems science, and philosophy.
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(Information-Gap Decision Theory presents a distinctive ne...)
Information-Gap Decision Theory presents a distinctive new theory of decision-making under severe uncertainty. Applications in engineering design and analysis, project management, economics, strategic planning, social decision making, environmental management, medical decisions, search and evasion problems, risk assessment, and other areas are discussed. Info-gap theory deals with many of the problems and questions of classical decision analysis such as risk assessment, gambling, value of information, trade-off analysis, and preference reversal, but the distinctive character of info-gap uncertainty repeatedly gives rise to new insights and unique decision algorithms. Furthermore, this book deals with many of the difficult interface issues facing the responsible decision maker such as value judgments concerning risk and immunity to failure, as well as philosophical implications of decision under uncertainty. This book is a fresh approach to the age-old problem of deciding responsibly with deficient information. An info-gap is the disparity between what is known and what needs to be known in order to make a well-founded decision. The book begins with a discussion of info-gap models of uncertainty, which provides an innovative approach to the quantification of severe lack of information. This book can be used in advanced undergraduate and graduate courses on decision theory and risk analysis. It is also of interest to practicing decision analysts and to researchers in decision theory and in human decision-making.
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(Recognition of the need to introduce the ideas of uncerta...)
Recognition of the need to introduce the ideas of uncertainty in a wide variety of scientific fields today reflects in part some of the profound changes in science and engineering over the last decades. Nobody questions the ever-present need for a solid foundation in applied mechanics. Neither does anyone question nowadays the fundamental necessity to recognize that uncertainty exists, to learn to evaluate it rationally, and to incorporate it into design. This volume provides a timely and stimulating overview of the analysis of uncertainty in applied mechanics. It is not just one more rendition of the traditional treatment of the subject, nor is it intended to supplement existing structural engineering books. Its aim is to fill a gap in the existing professional literature by concentrating on the non-probabilistic model of uncertainty. It provides an alternative avenue for the analysis of uncertainty when only a limited amount of information is available. The first chapter briefly reviews probabilistic methods and discusses the sensitivity of the probability of failure to uncertain knowledge of the system. Chapter two discusses the mathematical background of convex modelling.
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(Approach your problems from the right end It isn't that t...)
Approach your problems from the right end It isn't that they can't see the solution. It is and begin with the answers. Then one day, that they can't see the problem. perhaps you will find the final question. G. K. Chesterton. The Scandal of Father 'The Hermit Clad in Crane Feathers' in R. Brown The point of a Pin'. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (nonĀ trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "experimental mathematics", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics.
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researcher Mechanical engineering educator
Ben-Haim, Yakov was born on October 7, 1952 in Chicago, Illinois, United States. Son of John Paul and Muriel Moulton.
Bachelor, Beloit (Wisconsin) College, 1973; Master of Arts, University of California, Berkeley, 1978; Doctor of Philosophy, University of California, Berkeley, 1978.
Lecturer, Technion/Israel Institute Technology, Haifa, 1978-1985; senior lecturer, Technion/Israel Institute Technology, Haifa, 1985-1989; associate professor, Technion/Israel Institute Technology, Haifa, 1989-1998; professor mechanic engineering, Technion/Israel Institute Technology, Haifa, since 1998.
(Recognition of the need to introduce the ideas of uncerta...)
(The aim of the book is to develop methodology for reliabl...)
(Information-Gap Decision Theory presents a distinctive ne...)
(Approach your problems from the right end It isn't that t...)
(Everyone makes decisions, but not everyone is a decision ...)
(Uncertainty influences the individual as well as society....)
(Book by Ben-Haim, Yakov)
Fellow Japan Society for the Promotion of Science. Member Phi Beta Kappa (Yitzhak Modai chair technical and economics).
Married Miriam Rivka Ben-Haim, July 31, 1976. Children: Zvi, Eitan, Rafael.