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Decision Making Based On Convex Sets Of Probability Distributions
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Book Synopsis Decision Making Based on Convex Sets of Probability Distributions by : Fabio Cozman
Download or read book Decision Making Based on Convex Sets of Probability Distributions written by Fabio Cozman and published by . This book was released on 1997 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "The thesis advanced by this dissertation is that convex sets of probability distributions provide a powerful representational framework for decision making activities in Robotics and Artificial Intelligence. The primary contribution of this dissertation is the development of algorithms for inference and estimation in two domains. The first domain is robustness analysis for graphical models of inference. Novel results are developed for models that represent perturbations in Bayesian networks by convex sets of probability distributions. The dissertation reports on a system, called JavaBayes, that uniformly handles standard probability distributions and convex sets of probability distributions. This system is publicly available and has been used for teaching and research throughout the world. The second domain explored in this dissertation is outdoor visual position estimation for mobile robots. A novel algorithm for visual position estimation is derived in the context of remote driving for mobile robots in open, natural environments. This algorithm has been implemented in the Viper system, and field tested in a variety of environments, displaying accuracy and functionality levels that surpass previous work."
Book Synopsis Learning Convex Sets of Probability from Data by : Fabio Cozman
Download or read book Learning Convex Sets of Probability from Data written by Fabio Cozman and published by . This book was released on 1997 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Several theories of inference and decision employ sets of probability distributions as the fundamental representation of (subjective) belief. This paper investigates a frequentist connection between empirical data and convex sets of probability distributions. Building on earlier work by Walley and Fine, a framework is advanced in which a sequence of random outcomes can be described as being drawn from convex set of distributions, rather than just from a single distribution. The extra generality can be detected from observable characteristics of the outcome sequence. The paper presents new asymptotic convergence results paralleling the laws of large numbers in probability theory, and concludes with a comparison between this approach and approaches based on prior subjective constraints."
Book Synopsis Statistical Decision Rules and Optimal Inference by : N. N. Cencov
Download or read book Statistical Decision Rules and Optimal Inference written by N. N. Cencov and published by American Mathematical Soc.. This book was released on 2000-04-19 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: None available in plain English.
Book Synopsis Reflections on the Foundations of Probability and Statistics by : Thomas Augustin
Download or read book Reflections on the Foundations of Probability and Statistics written by Thomas Augustin and published by Springer Nature. This book was released on 2023-01-14 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Festschrift celebrates Teddy Seidenfeld and his seminal contributions to philosophy, statistics, probability, game theory and related areas. The 13 contributions in this volume, written by leading researchers in these fields, are supplemented by an interview with Teddy Seidenfeld that offers an abbreviated intellectual autobiography, touching on topics of timeless interest concerning truth and uncertainty. Indeed, as the eminent philosopher Isaac Levi writes in this volume: "In a world dominated by Alternative Facts and Fake News, it is hard to believe that many of us have spent our life’s work, as has Teddy Seidenfeld, in discussing truth and uncertainty." The reader is invited to share this celebration of Teddy Seidenfeld’s work uncovering truths about uncertainty and the penetrating insights they offer to our common pursuit of truth in the face of uncertainty.
Book Synopsis Theory of Games and Statistical Decisions by : David A. Blackwell
Download or read book Theory of Games and Statistical Decisions written by David A. Blackwell and published by Courier Corporation. This book was released on 2012-06-14 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evaluating statistical procedures through decision and game theory, as first proposed by Neyman and Pearson and extended by Wald, is the goal of this problem-oriented text in mathematical statistics. First-year graduate students in statistics and other students with a background in statistical theory and advanced calculus will find a rigorous, thorough presentation of statistical decision theory treated as a special case of game theory. The work of Borel, von Neumann, and Morgenstern in game theory, of prime importance to decision theory, is covered in its relevant aspects: reduction of games to normal forms, the minimax theorem, and the utility theorem. With this introduction, Blackwell and Professor Girshick look at: Values and Optimal Strategies in Games; General Structure of Statistical Games; Utility and Principles of Choice; Classes of Optimal Strategies; Fixed Sample-Size Games with Finite Ω and with Finite A; Sufficient Statistics and the Invariance Principle; Sequential Games; Bayes and Minimax Sequential Procedures; Estimation; and Comparison of Experiments. A few topics not directly applicable to statistics, such as perfect information theory, are also discussed. Prerequisites for full understanding of the procedures in this book include knowledge of elementary analysis, and some familiarity with matrices, determinants, and linear dependence. For purposes of formal development, only discrete distributions are used, though continuous distributions are employed as illustrations. The number and variety of problems presented will be welcomed by all students, computer experts, and others using statistics and game theory. This comprehensive and sophisticated introduction remains one of the strongest and most useful approaches to a field which today touches areas as diverse as gambling and particle physics.
Book Synopsis Introduction to the Scenario Approach by : Marco C. Campi
Download or read book Introduction to the Scenario Approach written by Marco C. Campi and published by SIAM. This book was released on 2018-11-15 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making decisions driven by experience. In this context, a scenario is an observation that comes from the environment, and scenario optimization refers to optimizing decisions over a set of available scenarios. Scenario optimization can be applied across a variety of fields, including machine learning, quantitative finance, control, and identification. This concise, practical book provides readers with an easy access point to make the scenario approach understandable to nonexperts, and offers an overview of various decision frameworks in which the method can be used. It contains numerous examples and diverse applications from a broad range of domains, including systems theory, control, biomedical engineering, economics, and finance. Practitioners can find "easy-to-use recipes," while theoreticians will benefit from a rigorous treatment of the theoretical foundations of the method, making it an excellent starting point for scientists interested in doing research in this field. Introduction to the Scenario Approach will appeal to scientists working in optimization, practitioners working in myriad fields involving decision-making, and anyone interested in data-driven decision-making.
Book Synopsis Elementary Decision Theory by : Herman Chernoff
Download or read book Elementary Decision Theory written by Herman Chernoff and published by Courier Corporation. This book was released on 1986-01-01 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This well-respected introduction to statistics and statistical theory covers data processing, probability and random variables, utility and descriptive statistics, computation of Bayes strategies, models, testing hypotheses, and much more. 1959 edition.
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Eyke Hüllermeier
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Eyke Hüllermeier and published by Springer Science & Business Media. This book was released on 2010-06-25 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.
Book Synopsis Scalable Uncertainty Management by : Eyke Hüllermeier
Download or read book Scalable Uncertainty Management written by Eyke Hüllermeier and published by Springer. This book was released on 2012-09-11 with total page 662 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Scalable Uncertainty Management, SUM 2012, held in Marburg, Germany, in September 2012. The 41 revised full papers and 13 revised short papers were carefully reviewed and selected from 75 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.
Book Synopsis Mathematical Statistics by : Thomas S. Ferguson
Download or read book Mathematical Statistics written by Thomas S. Ferguson and published by Academic Press. This book was released on 2014-07-10 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Statistics: A Decision Theoretic Approach presents an investigation of the extent to which problems of mathematical statistics may be treated by decision theory approach. This book deals with statistical theory that could be justified from a decision-theoretic viewpoint. Organized into seven chapters, this book begins with an overview of the elements of decision theory that are similar to those of the theory of games. This text then examines the main theorems of decision theory that involve two more notions, namely the admissibility of a decision rule and the completeness of a class of decision rules. Other chapters consider the development of theorems in decision theory that are valid in general situations. This book discusses as well the invariance principle that involves groups of transformations over the three spaces around which decision theory is built. The final chapter deals with sequential decision problems. This book is a valuable resource for first-year graduate students in mathematics.
Book Synopsis Foundations of Quantization for Probability Distributions by : Siegfried Graf
Download or read book Foundations of Quantization for Probability Distributions written by Siegfried Graf and published by Springer. This book was released on 2007-05-06 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.
Book Synopsis Combining Fuzzy Imprecision with Probabilistic Uncertainty in Decision Making by : Mario Fedrizzi
Download or read book Combining Fuzzy Imprecision with Probabilistic Uncertainty in Decision Making written by Mario Fedrizzi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the literature of decision analysis it is traditional to rely on the tools provided by probability theory to deal with problems in which uncertainty plays a substantive role. In recent years, however, it has become increasingly clear that uncertainty is a mul tifaceted concept in which some of the important facets do not lend themselves to analysis by probability-based methods. One such facet is that of fuzzy imprecision, which is associated with the use of fuzzy predicates exemplified by small, large, fast, near, likely, etc. To be more specific, consider a proposition such as "It is very unlikely that the price of oil will decline sharply in the near future," in which the italicized words play the role of fuzzy predicates. The question is: How can one express the mean ing of this proposition through the use of probability-based methods? If this cannot be done effectively in a probabilistic framework, then how can one employ the information provided by the proposition in question to bear on a decision relating to an investment in a company engaged in exploration and marketing of oil? As another example, consider a collection of rules of the form "If X is Ai then Y is B,," j = 1, . . . , n, in which X and Yare real-valued variables and Ai and Bi are fuzzy numbers exemplified by small, large, not very small, close to 5, etc.
Book Synopsis Convex Optimization by : Stephen P. Boyd
Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.
Book Synopsis Symbolic and Quantitative Approaches to Reasoning with Uncertainty by : Khaled Mellouli
Download or read book Symbolic and Quantitative Approaches to Reasoning with Uncertainty written by Khaled Mellouli and published by Springer. This book was released on 2007-09-14 with total page 927 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2007. Coverage in the 78 revised full papers, presented together with three invited papers, includes Bayesian networks, graphical models, learning causal networks, planning, causality and independence, preference modeling and decision, argumentation systems, inconsistency handling, and uncertainty measures.
Book Synopsis Decision Making Process by : Denis Bouyssou
Download or read book Decision Making Process written by Denis Bouyssou and published by John Wiley & Sons. This book was released on 2013-05-10 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the main methods and results in the formal study of the human decision-making process, as defined in a relatively wide sense. A key aim of the approach contained here is to try to break down barriers between various disciplines encompassed by this field, including psychology, economics and computer science. All these approaches have contributed to progress in this very important and much-studied topic in the past, but none have proved sufficient so far to define a complete understanding of the highly complex processes and outcomes. This book provides the reader with state-of-the-art coverage of the field, essentially forming a roadmap to the field of decision analysis. The first part of the book is devoted to basic concepts and techniques for representing and solving decision problems, ranging from operational research to artificial intelligence. Later chapters provide an extensive overview of the decision-making process under conditions of risk and uncertainty. Finally, there are chapters covering various approaches to multi-criteria decision-making. Each chapter is written by experts in the topic concerned, and contains an extensive bibliography for further reading and reference.
Book Synopsis Stochastic Orders and Decision Under Risk by : Karl C. Mosler
Download or read book Stochastic Orders and Decision Under Risk written by Karl C. Mosler and published by IMS. This book was released on 1991 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Decision Theory by : Lionel Weiss
Download or read book Statistical Decision Theory written by Lionel Weiss and published by . This book was released on 1961 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
