Advances In Decision Making Under Risk And Uncertainty
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Advances in Decision Making Under Risk and Uncertainty by Mohammed Abdellaoui,John D. Hey Pdf
Whether we like it or not we all feel that the world is uncertain. From choosing a new technology to selecting a job, we rarely know in advance what outcome will result from our decisions. Unfortunately, the standard theory of choice under uncertainty developed in the early forties and fifties turns out to be too rigid to take many tricky issues of choice under uncertainty into account. The good news is that we have now moved away from the early descriptively inadequate modeling of behavior. This book brings the reader into contact with the accomplished progress in individual decision making through the most recent contributions to uncertainty modeling and behavioral decision making. It also introduces the reader into the many subtle issues to be resolved for rational choice under uncertainty.
Decision Making Under Uncertainty by Mykel J. Kochenderfer Pdf
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Uncertainty in Risk Assessment, Risk Management, and Decision Making by V.T. Covello,Lester B. Lave,Alan Moghissi,V.R.R. Uppuluri Pdf
The subject of this volume--uncertainties in risk assessment and management--reflects an important theme in health, safety, and environ mental decision making. MOst technological hazards are characterized by substantial uncertainty. Recent examples include nuclear waste disposal, acid rain, asbestos in schools, carcinogens in food, and hazardous waste. realing with such uncertainty is arguably the most difficult and challeng ing task facing risk assessors and managers today. Four primary sources of uncertainty in risk assessment and management can be identified: (1) uncertainties about definitions; (2) uncertainties about scientific facts; (3) uncertainties about risk perceptions and atti tudes; and (4) uncertainties about values. Uncertainties about definitions derive primarily from disagreements about the meaning and interpretation of key concepts, such as probability. Uncertainties about scientific facts derive primarily from disagreements about failure modes, the probability and magnitude of adverse health or environmental consequences, cause and effect relationships, dose-response relationships, and exposure patterns. Uncertainties about risk perceptions and attitudes derive primarily from disagreements about what constitutes a significant or acceptable level of risk. Uncertainties about values derive primarily from disagreements about the desirability or worth of alternative risk management actions or conse quences. The papers in this volume address each of these sources of uncertainty from a variety of perspectives. Reflecting the broad scope of risk assess ment and risk management research, the papers include contributions from safety engineers, epidemiologists, toxicologists, chemists, biostatisticians, biologists, decision analysts, economists, psychologists, political scien tists, sociologists, ethicists, and lawyers.
Advanced Models and Tools for Effective Decision Making Under Uncertainty and Risk Contexts by González-Prida, Vicente,Carnero, María Carmen Pdf
Business industries depend on advanced models and tools that provide an optimal and objective decision-making process, ultimately guaranteeing improved competitiveness, reducing risk, and eliminating uncertainty. Thanks in part to the digital era of the modern world, reducing these conditions has become much more manageable. Advanced Models and Tools for Effective Decision Making Under Uncertainty and Risk Contexts provides research exploring the theoretical and practical aspects of effective decision making based not only on mathematical techniques, but also on those technological tools that are available nowadays in the Fourth Industrial Revolution. Featuring coverage on a broad range of topics such as industrial informatics, knowledge management, and production planning, this book is ideally designed for decision makers, researchers, engineers, academicians, and students.
Advances in Decision Making Under Risk and Uncertainty by Mohammed Abdellaoui,John D. Hey Pdf
Brings the reader into contact with the accomplished progress in individual decision making through the contributions to uncertainty modeling and behavioral decision making. This work also introduces the reader to the subtle issues to be resolved for rational choice under uncertainty.
Affective Decision Making Under Uncertainty by Donald J. Brown Pdf
This book is an exploration of the ubiquity of ambiguity in decision-making under uncertainty. It presents various essays on behavioral economics and behavioral finance that draw on the theory of Black Swans (Taleb 2010), which argues for a distinction between unprecedented events in our past and unpredictable events in our future. The defining property of Black Swan random events is that they are unpredictable, i.e., highly unlikely random events. In this text, Mandelbrot’s (1972) operational definition of risky random unpredictable events is extended to Black Swan assets – assets for which the cumulative probability distribution or conditional probability distribution of random future asset returns is a power distribution. Ambiguous assets are assets for which the uncertainties of future returns are not risks. Consequently, there are two disjoint classes of Black Swan assets: Risky Black Swan assets and Ambiguous Black Swan assets, a new class of ambiguous assets with unpredictable random future outcomes. The text is divided into two parts, the first of which focuses on affective moods, introduces affective utility functions and discusses the ambiguity of Black Swans. The second part, which shifts the spotlight to affective equilibrium in asset markets, features chapters on affective portfolio analysis and Walrasian and Gorman Polar Form Equilibrium Inequalities. In order to gain the most from the book, readers should have completed the standard introductory graduate courses on microeconomics, behavioral finance, and convex optimization. The book is intended for advanced undergraduates, graduate students and post docs specializing in economic theory, experimental economics, finance, mathematics, computer science or data analysis.
Managing Risk and Uncertainty by Richard Friberg Pdf
A comprehensive framework for assessing strategies for managing risk and uncertainty, integrating theory and practice and synthesizing insights from many fields. This book offers a framework for making decisions under risk and uncertainty. Synthesizing research from economics, finance, decision theory, management, and other fields, the book provides a set of tools and a way of thinking that determines the relative merits of different strategies. It takes as its premise that we make better decisions if we use the whole toolkit of economics and related fields to inform our decision making. The text explores the distinction between risk and uncertainty and covers standard models of decision making under risk as well as more recent work on decision making under uncertainty, with a particular focus on strategic interaction. It also examines the implications of incomplete markets for managing under uncertainty. It presents four core strategies: a benchmark strategy (proceeding as if risk and uncertainty were low), a financial hedging strategy (valuable if there is much risk), an operational hedging strategy (valuable for conditions of much uncertainty), and a flexible strategy (valuable if there is much risk and/or uncertainty). The book then examines various aspects of these strategies in greater depth, building on empirical work in several different fields. Topics include price-setting, real options and Monte Carlo techniques, organizational structure, and behavioral biases. Many chapters include exercises and appendixes with additional material. The book can be used in graduate or advanced undergraduate courses in risk management, as a guide for researchers, or as a reference for management practitioners.
Advances in Decision Analysis by Ward Edwards,Ralph F. Miles Jr.,Detlof von Winterfeldt Pdf
By framing issues, identifying risks, eliciting stakeholder preferences, and suggesting alternative approaches, decision analysts can offer workable solutions in domains such as the environment, health and medicine, engineering and operations research, and public policy. This book reviews and extends the material typically presented in introductory texts. Not a single book covers the broad scope of decision analysis at this advanced level. It will be a valuable resource for academics and students in decision analysis as well as decision analysts and managers
Author : Louis Anthony Cox, Jr. Publisher : John Wiley & Sons Page : 328 pages File Size : 50,9 Mb Release : 2015-02-23 Category : Business & Economics ISBN : 9781118938898
Breakthroughs in Decision Science and Risk Analysis by Louis Anthony Cox, Jr. Pdf
Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.
Theory of Decision Under Uncertainty by Itzhak Gilboa Pdf
This book describes the classical axiomatic theories of decision under uncertainty, as well as critiques thereof and alternative theories. It focuses on the meaning of probability, discussing some definitions and surveying their scope of applicability. The behavioral definition of subjective probability serves as a way to present the classical theories, culminating in Savage's theorem. The limitations of this result as a definition of probability lead to two directions - first, similar behavioral definitions of more general theories, such as non-additive probabilities and multiple priors, and second, cognitive derivations based on case-based techniques.
Author : George G. Szpiro Publisher : Columbia University Press Page : 413 pages File Size : 44,8 Mb Release : 2020-01-07 Category : Business & Economics ISBN : 9780231550970
Risk, Choice, and Uncertainty by George G. Szpiro Pdf
At its core, economics is about making decisions. In the history of economic thought, great intellectual prowess has been exerted toward devising exquisite theories of optimal decision making in situations of constraint, risk, and scarcity. Yet not all of our choices are purely logical, and so there is a longstanding tension between those emphasizing the rational and irrational sides of human behavior. One strand develops formal models of rational utility maximizing while the other draws on what behavioral science has shown about our tendency to act irrationally. In Risk, Choice, and Uncertainty, George G. Szpiro offers a new narrative of the three-century history of the study of decision making, tracing how crucial ideas have evolved and telling the stories of the thinkers who shaped the field. Szpiro examines economics from the early days of theories spun from anecdotal evidence to the rise of a discipline built around elegant mathematics through the past half century’s interest in describing how people actually behave. Considering the work of Locke, Bentham, Jevons, Walras, Friedman, Tversky and Kahneman, Thaler, and a range of other thinkers, he sheds light on the vast scope of discovery since Bernoulli first proposed a solution to the St. Petersburg Paradox. Presenting fundamental mathematical theories in easy-to-understand language, Risk, Choice, and Uncertainty is a revelatory history for readers seeking to grasp the grand sweep of economic thought.
Information-gap Decision Theory by Yakov Ben-Haim Pdf
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.
Advanced Decision Making by John Band,Lesley Partridge Pdf
This title looks at decision making from the manager’s viewpoint and aims to help you to improve your decision making. It also recognises that, in business today, decision making is everyone’s responsibility. Decision making for staff, who are not managers, is often through involvement in team decisions and the module also explores the benefits and limitations of team decision making.
Social and Economic Factors in Decision Making under Uncertainty by Kinga Posadzy Pdf
The objective of this thesis is to improve the understanding of human behavior that goes beyond monetary rewards. In particular, it investigates social influences in individual’s decision making in situations that involve coordination, competition, and deciding for others. Further, it compares how monetary and social outcomes are perceived. The common theme of all studies is uncertainty. The first four essays study individual decisions that have uncertain consequences, be it due to the actions of others or chance. The last essay, in turn, uses the advances in research on decision making under uncertainty to predict behavior in riskless choices. The first essay, Fairness Versus Efficiency: How Procedural Fairness Concerns Affect Coordination, investigates whether preferences for fair rules undermine the efficiency of coordination mechanisms that put some individuals at a disadvantage. The results from a laboratory experiment show that the existence of coordination mechanisms, such as action recommendations, increases efficiency, even if one party is strongly disadvantaged by the mechanism. Further, it is demonstrated that while individuals’ behavior does not depend on the fairness of the coordination mechanism, their beliefs about people’s behavior do. The second essay, Dishonesty and Competition. Evidence from a stiff competition environment, explores whether and how the possibility to behave dishonestly affects the willingness to compete and who the winner is in a competition between similarly skilled individuals. We do not find differences in competition entry between competitions in which dishonesty is possible and in which it is not. However, we find that due to the heterogeneity in propensity to behave dishonestly, around 20% of winners are not the best-performing individuals. This implies that the efficient allocation of resources cannot be ensured in a stiff competition in which behavior is unmonitored. The third essay, Tracing Risky Decision Making for Oneself and Others: The Role of Intuition and Deliberation, explores how individuals make choices under risk for themselves and on behalf of other people. The findings demonstrate that while there are no differences in preferences for taking risks when deciding for oneself and for others, individuals have greater decision error when choosing for other individuals. The differences in the decision error can be partly attributed to the differences in information processing; individuals employ more deliberative cognitive processing when deciding for themselves than when deciding for others. Conducting more information processing when deciding for others is related to the reduction in decision error. The fourth essay, The Effect of Decision Fatigue on Surgeons’ Clinical Decision Making, investigates how mental depletion, caused by a long session of decision making, affects surgeon’s decision to operate. Exploiting a natural experiment, we find that surgeons are less likely to schedule an operation for patients who have appointment late during the work shift than for patients who have appointment at the beginning of the work shift. Understanding how the quality of medical decisions depends on when the patient is seen is important for achieving both efficiency and fairness in health care, where long shifts are popular. The fifth essay, Preferences for Outcome Editing in Monetary and Social Contexts, compares whether individuals use the same rules for mental representation of monetary outcomes (e.g., purchases, expenses) as for social outcomes (e.g., having nice time with friends). Outcome editing is an operation in mental accounting that determines whether individuals prefer to first combine multiple outcomes before their evaluation (integration) or evaluate each outcome separately (segregation). I find that the majority of individuals express different preferences for outcome editing in the monetary context than in the social context. Further, while the results on the editing of monetary outcomes are consistent with theoretical predictions, no existing model can explain the editing of social outcomes.
Vincent A. W. J. Marchau,Warren E. Walker,Pieter J. T. M. Bloemen,Steven W. Popper
Author : Vincent A. W. J. Marchau,Warren E. Walker,Pieter J. T. M. Bloemen,Steven W. Popper Publisher : Springer Page : 408 pages File Size : 43,6 Mb Release : 2019-04-04 Category : Business & Economics ISBN : 9783030052522
Decision Making under Deep Uncertainty by Vincent A. W. J. Marchau,Warren E. Walker,Pieter J. T. M. Bloemen,Steven W. Popper Pdf
This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.