Download or read book Possibility for Decision written by Christer Carlsson and published by Springer Science & Business Media. This book was released on 2011-07-25 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book starts with the basic concepts of fuzzy sets and progresses through a normative view on possibility distributions and OWA operators in multiple criteria decisions. Five applications (that all build on experience from solving complex real world problems) of possibility distributions to strategic decisions about closing/not closing a production plant using fuzzy real options, portfolio selection with imprecise future data, predictive probabilities and possibilities for risk assessment in grid computing, fuzzy ontologies for process industry, and design (and implementation) of mobile value services are presented and carefully discussed. It can be useful for researchers and students working in soft computing, real options, fuzzy decision making, grid computing, knowledge mobilization and mobile value services.
Download or read book Multiperson Decision Making Models Using Fuzzy Sets and Possibility Theory written by J. Kacprzyk and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making is certainly a very crucial component of many human activities. It is, therefore, not surprising that models of decisions play a very important role not only in decision theory but also in areas such as operations Research, Management science, social Psychology etc . . The basic model of a decision in classical normative decision theory has very little in common with real decision making: It portrays a decision as a clear-cut act of choice, performed by one individual decision maker and in which states of nature, possible actions, results and preferences are well and crisply defined. The only compo nent in which uncertainty is permitted is the occurence of the different states of nature, for which probabilistic descriptions are allowed. These probabilities are generally assumed to be known numerically, i. e. as single probabili ties or as probability distribution functions. Extensions of this basic model can primarily be conceived in three directions: 1. Rather than a single decision maker there are several decision makers involved. This has lead to the areas of game theory, team theory and group decision theory. 2. The preference or utility function is not single valued but rather vector valued. This extension is considered in multiattribute utility theory and in multicritieria analysis. 3.
Download or read book Decision Theory with a Human Face written by Richard Bradley and published by Cambridge University Press. This book was released on 2017-10-26 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores how decision-makers can manage uncertainty that varies in both kind and severity by extending and supplementing Bayesian decision theory.
Download or read book The Paradox of Choice written by Barry Schwartz and published by Harper Collins. This book was released on 2009-10-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether we're buying a pair of jeans, ordering a cup of coffee, selecting a long-distance carrier, applying to college, choosing a doctor, or setting up a 401(k), everyday decisions—both big and small—have become increasingly complex due to the overwhelming abundance of choice with which we are presented. As Americans, we assume that more choice means better options and greater satisfaction. But beware of excessive choice: choice overload can make you question the decisions you make before you even make them, it can set you up for unrealistically high expectations, and it can make you blame yourself for any and all failures. In the long run, this can lead to decision-making paralysis, anxiety, and perpetual stress. And, in a culture that tells us that there is no excuse for falling short of perfection when your options are limitless, too much choice can lead to clinical depression. In The Paradox of Choice, Barry Schwartz explains at what point choice—the hallmark of individual freedom and self-determination that we so cherish—becomes detrimental to our psychological and emotional well-being. In accessible, engaging, and anecdotal prose, Schwartz shows how the dramatic explosion in choice—from the mundane to the profound challenges of balancing career, family, and individual needs—has paradoxically become a problem instead of a solution. Schwartz also shows how our obsession with choice encourages us to seek that which makes us feel worse. By synthesizing current research in the social sciences, Schwartz makes the counter intuitive case that eliminating choices can greatly reduce the stress, anxiety, and busyness of our lives. He offers eleven practical steps on how to limit choices to a manageable number, have the discipline to focus on those that are important and ignore the rest, and ultimately derive greater satisfaction from the choices you have to make.
Download or read book Utility Probability and Human Decision Making written by Dirk Wendt and published by Springer Science & Business Media. This book was released on 1975-12-31 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human decision making involves problems which are being studied with increasing interest and sophistication. They range from controversial political decisions via individual consumer decisions to such simple tasks as signal discriminations. Although it would seem that decisions have to do with choices among available actions of any kind, there is general agreement that decision making research should pertain to choice prob lems which cannot be solved without a predecisional stage of finding choice alternatives, weighing evidence, and judging values. The ultimate objective of scientific research on decision making is two-fold: (a) to develop a theoretically sound technology for the optimal solution of decision problems, and (b) to formulate a descriptive theory of human decision making. The latter may, in tum, protect decision makers from being caught in the traps of their own limitations and biases. Recently, in decision making research the strong emphasis on well defined laboratory tasks is decreasing in favour of more realistic studies in various practical settings. This may well have been caused by a growing awareness of the fact that decision-behaviour is strongly determined by situational factors, which makes it necessary to look into processes of interaction between the decision maker and the relevant task environ ment. Almost inevitably there is a parallel shift of interest towards problems of utility measurement and the evaluation of consequences.
Download or read book Decision Probability and Utility written by Peter Gärdenfors and published by Cambridge University Press. This book was released on 1988-04-29 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision theory and the theory of rational choice have recently been the subjects of considerable research by philosophers and economists. However, no adequate anthology exists which can be used to introduce students to the field. This volume is designed to meet that need. The essays included are organized into five parts covering the foundations of decision theory, the conceptualization of probability and utility, pholosophical difficulties with the rules of rationality and with the assessment of probability, and causal decision theory. The editors provide an extensive introduction to the field and introductions to each part.
Download or read book Elementary Decision Theory written by Herman Chernoff and published by Courier Corporation. This book was released on 2012-04-26 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The text is very clearly written [with] many illustrative examples and exercises [and] should be considered by those instructors who would like to introduce a more modern (and a more logical) approach in a basic course in statistics." —Journal of the American Statistical Association This volume is a well-known, well-respected introduction to a lively area of statistics. Professors Chernoff and Moses bring years of professional expertise as classroom teachers to this straightforward approach to statistical problems. And happily, for beginning students, they have by-passed involved computational reasonings which would only confuse the mathematical novice. Developed from nine years of teaching statistics at Stanford, the book furnishes a simple and clear-cut method of exhibiting the fundamental aspects of a statistical problem. Beginners will find this book a motivating introduction to important mathematical notions such as set, function and convexity. Examples and exercises throughout introduce new topics and ideas. The first seven chapters are recommended for beginning courses in the basic ideas of statistics and require only a knowledge of high school math. These sections include material on data processing, probability and random variables, utility and descriptive statistics, uncertainty due to ignorance of the state of nature, computing Bayes strategies and an introduction to classical statistics. The last three chapters review mathematical models and summarize terminology and methods of testing hypotheses. Tables and appendixes provide information on notation, shortcut computational formulas, axioms of probability, properties of expectations, likelihood ratio test, game theory, and utility functions. Authoritative, yet elementary in its approach to statistics and statistical theory, this work is also concise, well-indexed and abundantly equipped with exercise material. Ideal for a beginning course, this modestly priced edition will be especially valuable to those interested in the principles of statistics and scientific method.
Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Theory of Decision Under Uncertainty written by Itzhak Gilboa and published by Cambridge University Press. This book was released on 2009-03-16 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Logic of Decision written by Richard C. Jeffrey and published by . This book was released on 1965 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Statistical Decision Theory written by John Winsor Pratt and published by MIT Press. This book was released on 1995 with total page 906 pages. Available in PDF, EPUB and Kindle. Book excerpt: They then examine the Bernoulli, Poisson, and Normal (univariate and multivariate) data generating processes.
Download or read book Introduction to Probability and Statistical Decision Theory written by George Hadley and published by . This book was released on 1967 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision Trees for Decision Making written by John F. Magee and published by . This book was released on 1964 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision Theory and Decision Analysis Trends and Challenges written by Sixto Ríos and published by Springer Science & Business Media. This book was released on 1994-07-31 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Theory and Decision Analysis: Trends and Challenges is divided into three parts. The first part, overviews, provides state-of-the-art surveys of various aspects of decision analysis and utility theory. The second part, theory and foundations, includes theoretical contributions on decision-making under uncertainty, partial beliefs and preferences. The third section, applications, reflects the real possibilities of recent theoretical developments such as non-expected utility theories, multicriteria decision techniques, and how these improve our understanding of other areas including artificial intelligence, economics, and environmental studies.
Download or read book The Foundations of Causal Decision Theory written by James M. Joyce and published by Cambridge University Press. This book was released on 1999-04-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book also contains a major new discussion of what it means to suppose that some event occurs or that some proposition is true.
Download or read book Foundations of Decision making Agents written by Subrata Kumar Das and published by World Scientific. This book was released on 2008 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This self-contained book provides three fundamental and generic approaches (logical, probabilistic, and modal) to representing and reasoning with agent epistemic states, specifically in the context of decision making. Each of these approaches can be applied to the construction of intelligent software agents for making decisions, thereby creating computational foundations for decision-making agents. In addition, the book introduces a formal integration of the three approaches into a single unified approach that combines the advantages of all the approaches. Finally, the symbolic argumentation approach to decision making developed in this book, combining logic and probability, offers several advantages over the traditional approach to decision making which is based on simple rule-based expert systems or expected utility theory.
Download or read book Algorithms for Decision Making written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2022-08-16 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
