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Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Mykel J. Kochenderfer
Publisher: MIT Press
Total Pages: 350
Release: 2015-07-24
Genre: Computers
ISBN: 0262331713

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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.


Decision Making Under Uncertainty in Electricity Markets

Decision Making Under Uncertainty in Electricity Markets
Author: Antonio J. Conejo
Publisher: Springer Science & Business Media
Total Pages: 549
Release: 2010-09-08
Genre: Business & Economics
ISBN: 1441974210

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Decision Making Under Uncertainty in Electricity Markets provides models and procedures to be used by electricity market agents to make informed decisions under uncertainty. These procedures rely on well established stochastic programming models, which make them efficient and robust. Particularly, these techniques allow electricity producers to derive offering strategies for the pool and contracting decisions in the futures market. Retailers use these techniques to derive selling prices to clients and energy procurement strategies through the pool, the futures market and bilateral contracting. Using the proposed models, consumers can derive the best energy procurement strategies using the available trading floors. The market operator can use the techniques proposed in this book to clear simultaneously energy and reserve markets promoting efficiency and equity. The techniques described in this book are of interest for professionals working on energy markets, and for graduate students in power engineering, applied mathematics, applied economics, and operations research.


Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Charles A. Holloway
Publisher: Prentice Hall
Total Pages: 554
Release: 1979
Genre: Business & Economics
ISBN:

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Introduction and basic concepts; Models and probability; Choices and preferences; Preference assessment procedures; Behavioral assumptions and limitations of decision analysis; Risk sharing and incentives; Choices with multiple attributes.


Theory of Decision Under Uncertainty

Theory of Decision Under Uncertainty
Author: Itzhak Gilboa
Publisher: Cambridge University Press
Total Pages: 216
Release: 2009-03-16
Genre: Business & Economics
ISBN: 052151732X

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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.


Principles of Risk Analysis

Principles of Risk Analysis
Author: Charles Yoe
Publisher: CRC Press
Total Pages: 576
Release: 2016-04-19
Genre: Technology & Engineering
ISBN: 1439857504

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In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know-and it is intentional in the way it addresses the importance of the things we don't know. Principles of Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis i


Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Claude Greengard
Publisher: Springer Science & Business Media
Total Pages: 166
Release: 2012-12-06
Genre: Mathematics
ISBN: 146849256X

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In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.


Affective Decision Making Under Uncertainty

Affective Decision Making Under Uncertainty
Author: Donald J. Brown
Publisher: Springer Nature
Total Pages: 88
Release: 2020-12-18
Genre: Business & Economics
ISBN: 3030595129

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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.


Decision Making Under Uncertainty with RISKOptimizer

Decision Making Under Uncertainty with RISKOptimizer
Author: Wayne L. Winston
Publisher:
Total Pages: 0
Release: 1999
Genre: Decision making
ISBN: 9781893281011

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Previously published by Palisade Corporation, 1999 under the title: Decision making under uncertainty with RISKOptimizer : a step-by-step guide with Microsoft Excel and Palisade's RISKOptimizer software.


Radical Uncertainty: Decision-Making Beyond the Numbers

Radical Uncertainty: Decision-Making Beyond the Numbers
Author: John Kay
Publisher: W. W. Norton & Company
Total Pages: 407
Release: 2020-03-17
Genre: Business & Economics
ISBN: 1324004789

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Much economic advice is bogus quantification, warn two leading experts in this essential book, now with a preface on COVID-19. Invented numbers offer a false sense of security; we need instead robust narratives that give us the confidence to manage uncertainty. “An elegant and careful guide to thinking about personal and social economics, especially in a time of uncertainty. The timing is impeccable." — Christine Kenneally, New York Times Book Review Some uncertainties are resolvable. The insurance industry’s actuarial tables and the gambler’s roulette wheel both yield to the tools of probability theory. Most situations in life, however, involve a deeper kind of uncertainty, a radical uncertainty for which historical data provide no useful guidance to future outcomes. Radical uncertainty concerns events whose determinants are insufficiently understood for probabilities to be known or forecasting possible. Before President Barack Obama made the fateful decision to send in the Navy Seals, his advisers offered him wildly divergent estimates of the odds that Osama bin Laden would be in the Abbottabad compound. In 2000, no one—not least Steve Jobs—knew what a smartphone was; how could anyone have predicted how many would be sold in 2020? And financial advisers who confidently provide the information required in the standard retirement planning package—what will interest rates, the cost of living, and your state of health be in 2050?—demonstrate only that their advice is worthless. The limits of certainty demonstrate the power of human judgment over artificial intelligence. In most critical decisions there can be no forecasts or probability distributions on which we might sensibly rely. Instead of inventing numbers to fill the gaps in our knowledge, we should adopt business, political, and personal strategies that will be robust to alternative futures and resilient to unpredictable events. Within the security of such a robust and resilient reference narrative, uncertainty can be embraced, because it is the source of creativity, excitement, and profit.


Stochastic Dominance

Stochastic Dominance
Author: Haim Levy
Publisher: Springer Science & Business Media
Total Pages: 439
Release: 2006-08-25
Genre: Business & Economics
ISBN: 0387293116

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This book is devoted to investment decision-making under uncertainty. The book covers three basic approaches to this process: the stochastic dominance approach; the mean-variance approach; and the non-expected utility approach, focusing on prospect theory and its modified version, cumulative prospect theory. Each approach is discussed and compared. In addition, this volume examines cases in which stochastic dominance rules coincide with the mean-variance rule and considers how contradictions between these two approaches may occur.