Decision Making with Imperfect Decision Makers
Decision Making with Imperfect Decision Makers

Author: Tatiana Valentine Guy

Publisher: Springer Science & Business Media

Published: 2011-11-13

Total Pages: 207

ISBN-13: 3642246478

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Prescriptive Bayesian decision making has reached a high level of maturity and is well-supported algorithmically. However, experimental data shows that real decision makers choose such Bayes-optimal decisions surprisingly infrequently, often making decisions that are badly sub-optimal. So prevalent is such imperfect decision-making that it should be accepted as an inherent feature of real decision makers living within interacting societies. To date such societies have been investigated from an economic and gametheoretic perspective, and even to a degree from a physics perspective. However, little research has been done from the perspective of computer science and associated disciplines like machine learning, information theory and neuroscience. This book is a major contribution to such research. Some of the particular topics addressed include: How should we formalise rational decision making of a single imperfect decision maker? Does the answer change for a system of imperfect decision makers? Can we extend existing prescriptive theories for perfect decision makers to make them useful for imperfect ones? How can we exploit the relation of these problems to the control under varying and uncertain resources constraints as well as to the problem of the computational decision making? What can we learn from natural, engineered, and social systems to help us address these issues?

Decision Theory With Imperfect Information
Decision Theory With Imperfect Information

Author: Aliev Rafig Aziz

Publisher: World Scientific

Published: 2014-08-08

Total Pages: 468

ISBN-13: 9814611050

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Every day decision making in complex human-centric systems are characterized by imperfect decision-relevant information. The principal problems with the existing decision theories are that they do not have capability to deal with situations in which probabilities and events are imprecise. In this book, we describe a new theory of decision making with imperfect information. The aim is to shift the foundation of decision analysis and economic behavior from the realm bivalent logic to the realm fuzzy logic and Z-restriction, from external modeling of behavioral decisions to the framework of combined states.This book will be helpful for professionals, academics, managers and graduate students in fuzzy logic, decision sciences, artificial intelligence, mathematical economics, and computational economics.

Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions
Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions

Author: Rafik Aziz Aliev

Publisher: Springer

Published: 2013-01-12

Total Pages: 332

ISBN-13: 3642348955

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Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than computations over numbers and probabilities. The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision maker’s behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory. The book is self containing and represents in a systematic way the decision theory with imperfect information into the educational systems. The book will be helpful for teachers and students of universities and colleges, for managers and specialists from various fields of business and economics, production and social sphere.

Decision Making Under Uncertainty
Decision Making Under Uncertainty

Author: Mykel J. Kochenderfer

Publisher: MIT Press

Published: 2015-07-24

Total Pages: 350

ISBN-13: 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.

Theory of Decision Under Uncertainty
Theory of Decision Under Uncertainty

Author: Itzhak Gilboa

Publisher: Cambridge University Press

Published: 2009-03-16

Total Pages: 216

ISBN-13: 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.

Medical Decision Making
Medical Decision Making

Author: Harold C. Sox

Publisher: John Wiley & Sons

Published: 2013-05-08

Total Pages: 330

ISBN-13: 1118341562

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Medical Decision Making provides clinicians with a powerful framework for helping patients make decisions that increase the likelihood that they will have the outcomes that are most consistent with their preferences. This new edition provides a thorough understanding of the key decision making infrastructure of clinical practice and explains the principles of medical decision making both for individual patients and the wider health care arena. It shows how to make the best clinical decisions based on the available evidence and how to use clinical guidelines and decision support systems in electronic medical records to shape practice guidelines and policies. Medical Decision Making is a valuable resource for all experienced and learning clinicians who wish to fully understand and apply decision modelling, enhance their practice and improve patient outcomes. “There is little doubt that in the future many clinical analyses will be based on the methods described in Medical Decision Making, and the book provides a basis for a critical appraisal of such policies.” - Jerome P. Kassirer M.D., Distinguished Professor, Tufts University School of Medicine, US and Visiting Professor, Stanford Medical School, US

Decision Analysis, Game Theory, and Information
Decision Analysis, Game Theory, and Information

Author: Louis Kaplow

Publisher:

Published: 2004

Total Pages: 0

ISBN-13: 9781587788079

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Decision Analysis, Game Theory, and Information teaches the basics of decision analysis and game theory, the fundamental tools used over the past half-century by clients, whether businesses, government institutions, or other entities or individuals. Additionally, a brief introduction to basic concepts involving imperfect information concerning other parties are introduced. This handbook is designed for use as a supplementary test for a first-year course, and could also be used in connection with a course on legal methods or law and economics.This handbook comprises Chapters 1 and 2 of Analytical Methods for Lawyers, with appendix and revisions.

Decision Making Using Game Theory
Decision Making Using Game Theory

Author: Anthony Kelly

Publisher: Cambridge University Press

Published: 2003-03-27

Total Pages: 228

ISBN-13: 9781139438131

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Game theory is a key element in most decision-making processes involving two or more people or organisations. This book explains how game theory can predict the outcome of complex decision-making processes, and how it can help you to improve your own negotiation and decision-making skills. It is grounded in well-established theory, yet the wide-ranging international examples used to illustrate its application offer a fresh approach to an essential weapon in the armoury of the informed manager. The book is accessibly written, explaining in simple terms the underlying mathematics behind games of skill, before moving on to more sophisticated topics such as zero-sum games, mixed-motive games, and multi-person games, coalitions and power. Clear examples and helpful diagrams are used throughout, and the mathematics is kept to a minimum. It is written for managers, students and decision makers in any field.

Information Choice in Macroeconomics and Finance
Information Choice in Macroeconomics and Finance

Author: Laura L. Veldkamp

Publisher: Princeton University Press

Published: 2011-08-22

Total Pages: 181

ISBN-13: 140084049X

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An authoritative graduate textbook on information choice, an exciting frontier of research in economics and finance Most theories in economics and finance predict what people will do, given what they know about the world around them. But what do people know about their environments? The study of information choice seeks to answer this question, explaining why economic players know what they know—and how the information they have affects collective outcomes. Instead of assuming what people do or don't know, information choice asks what people would choose to know. Then it predicts what, given that information, they would choose to do. In this textbook, Laura Veldkamp introduces graduate students in economics and finance to this important new research. The book illustrates how information choice is used to answer questions in monetary economics, portfolio choice theory, business cycle theory, international finance, asset pricing, and other areas. It shows how to build and test applied theory models with information frictions. And it covers recent work on topics such as rational inattention, information markets, and strategic games with heterogeneous information. Illustrates how information choice is used to answer questions in monetary economics, portfolio choice theory, business cycle theory, international finance, asset pricing, and other areas Teaches how to build and test applied theory models with information frictions Covers recent research on topics such as rational inattention, information markets, and strategic games with heterogeneous information

Foundations of Info-metrics
Foundations of Info-metrics

Author: Amos Golan

Publisher: Oxford University Press

Published: 2018

Total Pages: 489

ISBN-13: 0199349525

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Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions that cannot be validated. In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrained optimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and case studies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines.