Dynamic Probabilistic Systems, Volume I: Markov Models (Dover Books on Mathematics Book 1)

Ronald A. Howard

Dover Publications

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.

Dynamic Probabilistic Systems, Volume I: Markov Models (Volume 1) (Dover Books on Mathematics)

Science & Math

Mathematics

Dover `

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 II: Semi-Markov and Decision Processes (Dover Books on Mathematics)

We often make small ethical compromises for "good" reasons: We lie to a customer because our boss asked us to. We exaggerate our accomplishments on our résumé to get an interview. Temptation blindsides us. And we make snap decisions we regret. Minor ethical lapses can seem harmless, but they instill in us a hard-to-break habit of distorted thinking. Rationalizations drown out our inner voice, and we make up the rules as we go. We lose control of our decisions, fall victim to the temptations and pressures of our situations, taint our characters, and sour business and personal relationships. In Ethics for the Real World, Ronald Howard and Clinton Korver explain how to master the art of ethical decision making by: Identifying potential compromises in your own life Applying distinctions to clarify your ethical thinking Committing in advance to ethical principles Generating creative alternatives to resolve dilemmas Packed with real-life examples, this book gives you practical advice to respond skillfully to life's inevitable ethical challenges. Not only can you make right decisions, you can acquire new habits that will realize the best in yourself and transform your relationships.

Ethics for the Real World: Creating a Personal Code to Guide Decisions in Work and Life

Business & Money

Clinton D. Korver

Business Culture

Harvard Business Review Press

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Books by Ronald A. Howard