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Decision Systems And Nonstochastic Randomness
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Book Synopsis Decision Systems and Nonstochastic Randomness by : V. I. Ivanenko
Download or read book Decision Systems and Nonstochastic Randomness written by V. I. Ivanenko and published by Springer Science & Business Media. This book was released on 2010-05-17 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Decision Systems and Non-stochastic Randomness" presents the first mathematical formalization of the statistical regularities of non-stochastic randomness and demonstrates how these regularities extend the standard probability-based model of decision making under uncertainty, allowing for the description of uncertain mass events that do not fit standard stochastic models. The formalism of statistical regularities developed in this book will have a significant influence on decision theory and information theory as well as numerous other disciplines.
Book Synopsis Continuous and Distributed Systems by : Mikhail Z. Zgurovsky
Download or read book Continuous and Distributed Systems written by Mikhail Z. Zgurovsky and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this volume, the authors close the gap between abstract mathematical approaches, such as abstract algebra, number theory, nonlinear functional analysis, partial differential equations, methods of nonlinear and multi-valued analysis, on the one hand, and practical applications in nonlinear mechanics, decision making theory and control theory on the other. Readers will also benefit from the presentation of modern mathematical modeling methods for the numerical solution of complicated engineering problems in hydromechanics, geophysics and mechanics of continua. This compilation will be of interest to mathematicians and engineers working at the interface of these field. It presents selected works of the open seminar series of Lomonosov Moscow State University and the National Technical University of Ukraine “Kyiv Polytechnic Institute”. The authors come from Germany, Italy, Spain, Russia, Ukraine, and the USA.
Book Synopsis Quantum Fractals: From Heisenberg's Uncertainty To Barnsley's Fractality by : Arkadiusz Jadczyk
Download or read book Quantum Fractals: From Heisenberg's Uncertainty To Barnsley's Fractality written by Arkadiusz Jadczyk and published by World Scientific. This book was released on 2014-07-23 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting with numerical algorithms resulting in new kinds of amazing fractal patterns on the sphere, this book describes the theory underlying these phenomena and indicates possible future applications. The book also explores the following questions:
Book Synopsis Universal Traceability. A Comprehensive, Generic, Technology-Independent, and Semantically Rich Approach by : Hannes Schwarz
Download or read book Universal Traceability. A Comprehensive, Generic, Technology-Independent, and Semantically Rich Approach written by Hannes Schwarz and published by Logos Verlag Berlin GmbH. This book was released on 2012 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traceability describes the ability of stakeholders to understand and follow relationships between artifacts that play some role in software development. It is essential for many development tasks, e.g., quality assurance, requirements management, or software maintenance. Aiming to overcome various deficiencies of existing traceability concepts, this book presents a universal approach describing required features of traceability solutions. This includes a technology-independent, generic template for the definition of semantically rich traceability relationship types and technology-independent patterns for the retrieval of traceability information, reflecting generic problems common to traceability applications. The universal approach is implemented on the basis of two concrete technologies which facilitate comprehensive traceability: the TGraph approach and OWL ontologies. The applicability of the approach is shown by three case studies dealing with the reuse of software artifacts, process model refinement, and requirements management, respectively.
Book Synopsis Systems Science: Theory, Analysis, Modeling, and Design by : George E. Mobus
Download or read book Systems Science: Theory, Analysis, Modeling, and Design written by George E. Mobus and published by Springer Nature. This book was released on 2022-03-09 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes a comprehensive approach to applying systems science formally to the deep analysis of a wide variety of complex systems. Detailed ‘how-to’ examples of the three phases (analysis-modeling-design) of systems science are applied to systems of various types (machines, organic (e.g. ecosystem), and supra-organic (e.g. business organizations and government). The complexity of the global system has reached proportions that seriously challenge our abilities to understand the consequences of our use of technology, modification of natural ecosystems, or even how to govern ourselves. For this reason, complex mathematics is eschewed when simpler structures will suffice, allowing the widest possible audience to apply and benefit from the available tools and concepts of systems science in their own work. The book shows, in detail, how to functionally and structurally deconstruct complex systems using a fundamental language of systems. It shows how to capture the discovered details in a structured knowledge base from which abstract models can be derived for simulation. The knowledge base is also shown to be a basis for generating system design specifications for human-built artifacts, or policy recommendations/policy mechanisms for socio-economic-ecological systems management. The book builds on principles and methods found in the authors’ textbook Principles of Systems Science (co-authored with Michael Kalton), but without prerequisites. It will appeal to a broad audience that deals with complex systems every day, from design engineers to economic and ecological systems managers and policymakers.
Book Synopsis Randomness and Elements of Decision Theory Applied to Signals by : Monica Borda
Download or read book Randomness and Elements of Decision Theory Applied to Signals written by Monica Borda and published by Springer. This book was released on 2022-12-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes
Download or read book Soviet Physics, Doklady written by and published by . This book was released on 1991 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Natural Resources, Uncertainty, and General Equilibrium Systems by : Alan S. Blinder
Download or read book Natural Resources, Uncertainty, and General Equilibrium Systems written by Alan S. Blinder and published by Elsevier. This book was released on 2013-10-22 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Resources, Uncertainty, and General Equilibrium Systems: Essays in Memory of Rafael Lusky compiles a collection of works by economists who had been friends and colleagues of Rafael Lusky, a teacher in the University of Florida and contributor to theoretical resource economics. This book is divided into four sections— natural resources, uncertainty, general equilibrium systems, and policy and applications. In these sections, this text specifically discusses the resource depletion with technological uncertainty and the Rawlsian fairness principle; monopoly, uncertainty, and exploration; and price discrimination under uncertainty. The insurance theoretic aspects of workers' compensation; adverse selection and optimum insurance policies; and difficulty with Keynesian models of aggregate demand are also elaborated. This compilation likewise deliberates the exchange model of bilateral trade; optimal taxes on foreign lending; and extended linear permanent expenditure system (ELPES). This publication is a useful reference for economists and students concerned with theoretical resource economics.
Book Synopsis Introduction to Multi-Armed Bandits by : Aleksandrs Slivkins
Download or read book Introduction to Multi-Armed Bandits written by Aleksandrs Slivkins and published by . This book was released on 2019-10-31 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-armed bandits is a rich, multi-disciplinary area that has been studied since 1933, with a surge of activity in the past 10-15 years. This is the first book to provide a textbook like treatment of the subject.
Book Synopsis Decision Making Under Uncertainty by : Mykel J. Kochenderfer
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.
Book Synopsis Applied Stochastic Differential Equations by : Simo Särkkä
Download or read book Applied Stochastic Differential Equations written by Simo Särkkä and published by Cambridge University Press. This book was released on 2019-05-02 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Book Synopsis Differential Equations by : K.D. Elworthy
Download or read book Differential Equations written by K.D. Elworthy and published by Routledge. This book was released on 2017-11-22 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents recent developments in the areas of differential equations, dynamical systems, and control of finke and infinite dimensional systems. Focuses on current trends in differential equations and dynamical system research-from Darameterdependence of solutions to robui control laws for inflnite dimensional systems.
Book Synopsis Reinforcement Learning and Stochastic Optimization by : Warren B. Powell
Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a “diary problem” that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.
Book Synopsis Probability for Machine Learning by : Jason Brownlee
Download or read book Probability for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-09-24 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more.
Download or read book Randomness written by Deborah J. Bennett and published by Harvard University Press. This book was released on 2009-07-01 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the ancients' first readings of the innards of birds to your neighbor's last bout with the state lottery, humankind has put itself into the hands of chance. Today life itself may be at stake when probability comes into play--in the chance of a false negative in a medical test, in the reliability of DNA findings as legal evidence, or in the likelihood of passing on a deadly congenital disease--yet as few people as ever understand the odds. This book is aimed at the trouble with trying to learn about probability. A story of the misconceptions and difficulties civilization overcame in progressing toward probabilistic thinking, Randomness is also a skillful account of what makes the science of probability so daunting in our own day. To acquire a (correct) intuition of chance is not easy to begin with, and moving from an intuitive sense to a formal notion of probability presents further problems. Author Deborah Bennett traces the path this process takes in an individual trying to come to grips with concepts of uncertainty and fairness, and also charts the parallel path by which societies have developed ideas about chance. Why, from ancient to modern times, have people resorted to chance in making decisions? Is a decision made by random choice fair? What role has gambling played in our understanding of chance? Why do some individuals and societies refuse to accept randomness at all? If understanding randomness is so important to probabilistic thinking, why do the experts disagree about what it really is? And why are our intuitions about chance almost always dead wrong? Anyone who has puzzled over a probability conundrum is struck by the paradoxes and counterintuitive results that occur at a relatively simple level. Why this should be, and how it has been the case through the ages, for bumblers and brilliant mathematicians alike, is the entertaining and enlightening lesson of Randomness.
Book Synopsis T.I.S.C.A. Technical Information Indexes by : United States. Naval Air Systems Command
Download or read book T.I.S.C.A. Technical Information Indexes written by United States. Naval Air Systems Command and published by . This book was released on 1975 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Prediction, Learning, and Games by : Nicolo Cesa-Bianchi
Download or read book Prediction, Learning, and Games written by Nicolo Cesa-Bianchi and published by Cambridge University Press. This book was released on 2006-03-13 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
