Decision Making Under Uncertainty And Reinforcement Learning

Author : Christos Dimitrakakis,Ronald Ortner
Publisher : Springer Nature
Page : 251 pages
File Size : 54,9 Mb
Release : 2022-12-02
Category : Technology & Engineering
ISBN : 9783031076145

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Decision Making Under Uncertainty and Reinforcement Learning by Christos Dimitrakakis,Ronald Ortner Pdf

This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.

Author : Mykel J. Kochenderfer
Publisher : MIT Press
Page : 350 pages
File Size : 43,5 Mb
Release : 2015-07-24
Category : Computers
ISBN : 9780262331715

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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.

Author : Anonim
Publisher : Unknown
Page : 323 pages
File Size : 43,9 Mb
Release : 2015
Category : Automatic machinery
ISBN : 0262331705

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Decision Making Under Uncertainty by Anonim Pdf

Author : Anonim
Publisher : Unknown
Page : 445 pages
File Size : 41,9 Mb
Release : 1974
Category : Electronic
ISBN : UOMDLP:ade4780:0001.001

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DECISION MAKING UNDER UNCERTAINTY: ECONOMIC EVALUATION OF STREAMFLOW FORECASTS by Anonim Pdf

Author : Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray
Publisher : MIT Press
Page : 701 pages
File Size : 47,6 Mb
Release : 2022-08-16
Category : Computers
ISBN : 9780262370233

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Algorithms for Decision Making by Mykel J. Kochenderfer,Tim A. Wheeler,Kyle H. Wray Pdf

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.

Author : Martine Ceberio,Vladik Kreinovich
Publisher : Springer Nature
Page : 286 pages
File Size : 54,7 Mb
Release : 2023-01-03
Category : Technology & Engineering
ISBN : 9783031164156

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Decision Making Under Uncertainty and Constraints by Martine Ceberio,Vladik Kreinovich Pdf

This book shows, on numerous examples, how to make decisions in realistic situations when we have both uncertainty and constraints. In most these situations, the book's emphasis is on the why-question, i.e., on a theoretical explanation for empirical formulas and techniques. Such explanations are important: they help understand why these techniques work well in some cases and not so well in others, and thus, help practitioners decide whether a technique is appropriate for a given situation. Example of applications described in the book ranges from science (biosciences, geosciences, and physics) to electrical and civil engineering, education, psychology and decision making, and religion—and, of course, include computer science, AI (in particular, eXplainable AI), and machine learning. The book can be recommended to researchers and students in these application areas. Many of the examples use general techniques that can be used in other application areas as well, so it is also useful for practitioners and researchers in other areas who are looking for possible theoretical explanations of empirical formulas and techniques.

Author : Laxman Bokati,Vladik Kreinovich
Publisher : Springer Nature
Page : 203 pages
File Size : 52,6 Mb
Release : 2023-03-21
Category : Technology & Engineering
ISBN : 9783031260865

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Decision Making Under Uncertainty, with a Special Emphasis on Geosciences and Education by Laxman Bokati,Vladik Kreinovich Pdf

This book describes new techniques for making decisions in situations with uncertainty and new applications of decision-making techniques. The main emphasis is on situations when it is difficult to decrease uncertainty. For example, it is very difficult to accurately predict human economic behavior, so in economics, it is very important to take this uncertainty into account when making decisions. Other areas where it is difficult to decrease uncertainty are geosciences and teaching. The book analyzes the general problem of decision making and shows how its results can be applied to economics, geosciences, and teaching. Since all these applications involve computing, the book also shows how these results can be applied to computing, including deep learning and quantum computing. The book is recommended to researchers, practitioners, and students who want to learn more about decision making under uncertainty—and who want to work on remaining challenges.

Author : Martijn van Otterlo
Publisher : IOS Press
Page : 508 pages
File Size : 45,8 Mb
Release : 2009
Category : Business & Economics
ISBN : 9781586039691

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The Logic of Adaptive Behavior by Martijn van Otterlo Pdf

Markov decision processes have become the de facto standard in modeling and solving sequential decision making problems under uncertainty. This book studies lifting Markov decision processes, reinforcement learning and dynamic programming to the first-order (or, relational) setting.

Author : Joe Lorkowski,Vladik Kreinovich
Publisher : Springer
Page : 164 pages
File Size : 46,7 Mb
Release : 2017-07-01
Category : Technology & Engineering
ISBN : 9783319622149

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Bounded Rationality in Decision Making Under Uncertainty: Towards Optimal Granularity by Joe Lorkowski,Vladik Kreinovich Pdf

This book addresses an intriguing question: are our decisions rational? It explains seemingly irrational human decision-making behavior by taking into account our limited ability to process information. It also shows with several examples that optimization under granularity restriction leads to observed human decision-making. Drawing on the Nobel-prize-winning studies by Kahneman and Tversky, researchers have found many examples of seemingly irrational decisions: e.g., we overestimate the probability of rare events. Our explanation is that since human abilities to process information are limited, we operate not with the exact values of relevant quantities, but with “granules” that contain these values. We show that optimization under such granularity indeed leads to observed human behavior. In particular, for the first time, we explain the mysterious empirical dependence of betting odds on actual probabilities. This book can be recommended to all students interested in human decision-making, to researchers whose work involves human decisions, and to practitioners who design and employ systems involving human decision-making —so that they can better utilize our ability to make decisions under uncertainty.

Author : Charles A. Holloway
Publisher : Prentice Hall
Page : 560 pages
File Size : 41,7 Mb
Release : 1979
Category : Business & Economics
ISBN : UOM:39015048596764

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Decision Making Under Uncertainty by Charles A. Holloway Pdf

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.

Author : Tatiana Valentine Guy,Miroslav Kárný,David H. Wolpert
Publisher : Springer Science & Business Media
Page : 195 pages
File Size : 49,6 Mb
Release : 2011-11-13
Category : Technology & Engineering
ISBN : 9783642246470

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Decision Making with Imperfect Decision Makers by Tatiana Valentine Guy,Miroslav Kárný,David H. Wolpert Pdf

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?

Author : Xizhao Wang,Junhai Zhai
Publisher : CRC Press
Page : 190 pages
File Size : 41,8 Mb
Release : 2016-11-25
Category : Business & Economics
ISBN : 9781315353562

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Learning with Uncertainty by Xizhao Wang,Junhai Zhai Pdf

Learning with uncertainty covers a broad range of scenarios in machine learning, this book mainly focuses on: (1) Decision tree learning with uncertainty, (2) Clustering under uncertainty environment, (3) Active learning based on uncertainty criterion, and (4) Ensemble learning in a framework of uncertainty. The book starts with the introduction to uncertainty including randomness, roughness, fuzziness and non-specificity and then comprehensively discusses a number of key issues in learning with uncertainty, such as uncertainty representation in learning, the influence of uncertainty on the performance of learning system, the heuristic design with uncertainty, etc. Most contents of the book are our research results in recent decades. The purpose of this book is to help the readers to understand the impact of uncertainty on learning processes. It comes with many examples to facilitate understanding. The book can be used as reference book or textbook for researcher fellows, senior undergraduates and postgraduates majored in computer science and technology, applied mathematics, automation, electrical engineering, etc.

Author : Kerstin Preuschoff,Peter N. C. Mohr,Ming Hsu
Publisher : Frontiers Media SA
Page : 144 pages
File Size : 55,5 Mb
Release : 2015-06-16
Category : Biological psychiatry
ISBN : 9782889194667

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Decision Making under Uncertainty by Kerstin Preuschoff,Peter N. C. Mohr,Ming Hsu Pdf

Most decisions in life are based on incomplete information and have uncertain consequences. To successfully cope with real-life situations, the nervous system has to estimate, represent and eventually resolve uncertainty at various levels. A common tradeoff in such decisions involves those between the magnitude of the expected rewards and the uncertainty of obtaining the rewards. For instance, a decision maker may choose to forgo the high expected rewards of investing in the stock market and settle instead for the lower expected reward and much less uncertainty of a savings account. Little is known about how different forms of uncertainty, such as risk or ambiguity, are processed and learned about and how they are integrated with expected rewards and individual preferences throughout the decision making process. With this Research Topic we aim to provide a deeper and more detailed understanding of the processes behind decision making under uncertainty.

Author : Tatiana Valentine Guy,M. Kárný,David H. Wolpert
Publisher : Unknown
Page : 184 pages
File Size : 40,9 Mb
Release : 2015
Category : Artificial intelligence
ISBN : 3319151452

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Decision Making by Tatiana Valentine Guy,M. Kárný,David H. Wolpert Pdf

This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selƠ̐lsh decision makers. The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making. Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems. In particular, analyses and experiments are presented which concern: ĺØ task allocation to maximize ĺlthe wisdom of the crowdĺl; ĺØ design of a society of ĺledutainmentĺl robots who account for one anothersĺl emotional states; ĺØ recognizing and counteracting seemingly non-rational human decision making; ĺØ coping with extreme scale when learning causality in networks; ĺØ efƠ̐lciently incorporating expert knowledge in personalized medicine; ĺØ the effects of personality on risky decision making. The volume is a valuable source for researchers, graduate students and practitioners in machine learning, stochastic control, robotics, and economics, among other Ơ̐lelds.

Author : Magda Osman
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 41,8 Mb
Release : 2011-07-18
Category : Psychology
ISBN : 9781444351804

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Controlling Uncertainty by Magda Osman Pdf

Controlling Uncertainty: Decision Making and Learning in Complex Worlds reviews and discusses the most current research relating to the ways we can control the uncertain world around us. Features reviews and discussions of the most current research in a number of fields relevant to controlling uncertainty, such as psychology, neuroscience, computer science and engineering Presents a new framework that is designed to integrate a variety of disparate fields of research Represents the first book of its kind to provide a general overview of work related to understanding control