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A two-volume set, consisting of the latest editions of the two volumes (4th edition (2017) for Vol. I, and 4th edition (2012) for Vol. II). Much supplementary material can be found at the book's web page. The first volume is oriented towards modeling, conceptualization, and finite-horizon problems, but also includes a substantive introduction to infinite horizon problems that is suitable for classroom use, as well as an up-to-date account of some of the most interesting developments in approximate dynamic programming. The second volume is oriented towards mathematical analysis and computation, treats infinite horizon problems extensively, and provides a detailed account of approximate large-scale dynamic programming and reinforcement learning. This is a textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. The treatment focuses on basic unifying themes, and conceptual foundations. It illustrates the versatility, power, and generality of the method with many examples and applications from engineering, operations research, and other fields. It also addresses extensively the practical application of the methodology, possibly through the use of approximations, and provides an introduction to the methodology of Neuro-Dynamic Programming, which is the focus of much recent research.

In terms of simple and complex systems, it is a whole new world out there. At the initial publication of this book, fourteen years ago, the web was in its infancy, DVDs did not exist, cell phones were few and far between, and the information superhighway was just a blip upon the horizon. If you used the terms "social engineering," you were most likely a political scientist, and if you were "phishing" you might be listening to a rock band. The second edition of a bestseller, Human Factors in Simple and Complex Systems provides the necessary understanding of the breadth and depth of human factors issues that influence the design, implementation, and evaluation of products and systems. Emphasizing the close relationship between basic theory and application, the authors delineate a framework for the research process, present an integrated view of the current state of knowledge, and examine how these factors can be applied to system design. The new edition addresses such concepts as situation awareness and highlights topics of interest, with a special focus on computer applications and human-computer interaction.See what’s new in the Second Edition New topics, such as situational awareness, that capture the tremendous changes in human factors and ergonomics Tightly integrates basic research and application, strengthening the link between knowledge and practice Each chapter includes a separate box that discusses a topic of current interest related to human interaction with computers and recent technology Demonstrating a general approach to solving a broad range of system problems, the book provides coverage of the theoretical foundation on which the discipline of human factors is built. Structured around human information processing, it covers the full range of contemporary human factors and ergonomics, then shows you how to apply them.

A two-volume set, consisting of the latest editions of the two volumes (4th edition (2017) for Vol. I, and 4th edition (2012) for Vol. II). Much supplementary material can be found at the book's web page. The first volume is oriented towards modeling, conceptualization, and finite-horizon problems, but also includes a substantive introduction to infinite horizon problems that is suitable for classroom use, as well as an up-to-date account of some of the most interesting developments in approximate dynamic programming. The second volume is oriented towards mathematical analysis and computation, treats infinite horizon problems extensively, and provides a detailed account of approximate large-scale dynamic programming and reinforcement learning. This is a textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. The treatment focuses on basic unifying themes, and conceptual foundations. It illustrates the versatility, power, and generality of the method with many examples and applications from engineering, operations research, and other fields. It also addresses extensively the practical application of the methodology, possibly through the use of approximations, and provides an introduction to the methodology of Neuro-Dynamic Programming, which is the focus of much recent research.