Decision Processes in Dynamic Probabilistic Systems


Book Description

'Et moi - ... - si j'avait su comment en revenir. One service mathematics has rendered the je n'y serais point aile: human race. It has put common sense back where it belongs. on the topmost shelf next Jules Verne (0 the dusty canister labelled 'discarded non sense'. The series is divergent; therefore we may be able to do something with it. Eric T. Bell O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics .. .'; 'One service logic has rendered com puter science .. .'; 'One service category theory has rendered mathematics .. .'. All arguably true. And all statements obtainable this way form part of the raison d'etre of this series.




Dynamic Probabilistic Systems, Volume II


Book Description

This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, continues his treatment from Volume I with surveys of the discrete- and continuous-time semi-Markov processes, continuous-time Markov processes, and the optimization procedure of dynamic programming. The final chapter reviews the preceding material, focusing on the decision processes with discussions of decision structure, value and policy iteration, and examples of infinite duration and transient processes. Volume II concludes with an appendix listing the properties of congruent matrix multiplication.







Dynamic Probabilistic Systems, Volume I


Book Description

This book is an integrated work published in two volumes. The first volume treats the basic Markov process and its variants; the second, semi-Markov and decision processes. Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing. More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory. Author Ronald A. Howard, Professor of Management Science and Engineering at Stanford University, begins with the basic Markov model, proceeding to systems analyses of linear processes and Markov processes, transient Markov processes and Markov process statistics, and statistics and inference. Subsequent chapters explore recurrent events and random walks, Markovian population models, and time-varying Markov processes. Volume I concludes with a pair of helpful indexes.







Theory and Applications of Dependable Computer Systems


Book Description

This book presents selected papers from the Fifteenth International Conference on Dependability of Computer Systems (DepCoS-RELCOMEX), which illustrate the diversity of theoretical problems in analysis of performability, reliability and security of contemporary computer systems. Covering also methodologies and practical tools involved in this field, it is a valuable reference resource for scientists, researchers, practitioners and students who are dealing with these subjects. Established in 2006, DepCoS-RELCOMEX is an annual conference series organised by Wrocław University of Science and Technology. It focuses on the dependability and performability of contemporary computer systems – topics that can provide solutions to new challenges in evaluation of their reliability and efficiency. Since they are probably the most complex technical systems ever engineered by humans, the organization of modern computer systems cannot be modelled and analysed solely as structures (however complex and distributed) built only on the basis of technical resources. Instead they should be considered as a unique blend of interacting people (their needs and behaviours), networks (together with mobile properties, iCloud organisation, Internet of Everything) and a large number of users dispersed geographically and producing an unimaginable number of applications. This new, interdisciplinary approach is developing a continually increasing range of methods which apply also the latest findings in artificial intelligence (AI) and computational intelligence (CI).




Applied Reliability Engineering and Risk Analysis


Book Description

This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field. With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century. Key features include: expert treatment of probabilistic models and statistical inference from leading scientists, researchers and practitioners in their respective reliability fields detailed coverage of multi-state system reliability, maintenance models, statistical inference in reliability, systemability, physics of failures and reliability demonstration many examples and engineering case studies to illustrate the theoretical results and their practical applications in industry Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume. It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and statistics, reliability engineering and maintenance, logistics, and quality control. It is also a useful resource for graduate students specialising in reliability analysis and applied probability and statistics. Dedicated to the Centennial of the birth of Boris Gnedenko, renowned Russian mathematician and reliability theorist




Reliability and Safety Assessment of Dynamic Process Systems


Book Description

Current issues and approaches in the reliability and safety analysis of dynamic process systems are the subject of this book. The authors of the chapters are experts from nuclear, chemical, mechanical, aerospace and defense system industries, and from institutions including universities, national laboratories, private consulting companies, and regulatory bodies. Both the conventional approaches and dynamic methodologies which explicitly account for the time element in system evolution in failure modeling are represented. The papers on conventional approaches concentrate on the modeling of dynamic effects and the need for improved methods. The dynamic methodologies covered include the DYLAM methodology, the theory of continuous event trees, several Markov model construction procedures, Monte Carlo simulation, and utilization of logic flowgraphs in conjunction with Petri nets. Special emphasis is placed on human factors such as procedures and training.




Nonlinearly Perturbed Semi-Markov Processes


Book Description

The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-Markov processes with a finite phase space. These methods are based on special time-space screening procedures for sequential phase space reduction of semi-Markov processes combined with the systematical use of operational calculus for Laurent asymptotic expansions. Effective recurrent algorithms are composed for getting asymptotic expansions, without and with explicit upper bounds for remainders, for power moments of hitting times, stationary and conditional quasi-stationary distributions for nonlinearly perturbed semi-Markov processes. These results are illustrated by asymptotic expansions for birth-death-type semi-Markov processes, which play an important role in various applications. The book will be a useful contribution to the continuing intensive studies in the area. It is an essential reference for theoretical and applied researchers in the field of stochastic processes and their applications that will contribute to continuing extensive studies in the area and remain relevant for years to come.




Partially Observed Markov Decision Processes


Book Description

This book covers formulation, algorithms, and structural results of partially observed Markov decision processes, whilst linking theory to real-world applications in controlled sensing. Computations are kept to a minimum, enabling students and researchers in engineering, operations research, and economics to understand the methods and determine the structure of their optimal solution.