Modeling and Simulation Fundamentals: Theoretical Underpinnings and Practical Domains (Repost)

An insightful presentation of the key concepts, paradigms, and applications of modeling and simulation Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. Modeling and Simulation Fundamentals offers a comprehensive and authoritative treatment of the topic and includes definitions, paradigms, and applications to equip readers with the skills needed to work successfully as developers and users of modeling and simulation. Featuring contributions written by leading experts in the field, the book's fluid presentation builds from topic to topic and provides the foundation and theoretical underpinnings of modeling and simulation. First, an introduction to the topic is presented, including related terminology, examples of model development, and various domains of modeling and simulation. Subsequent chapters develop the necessary mathematical background needed to understand modeling and simulation topics, model types, and the importance of visualization. In addition, Monte Carlo simulation, continuous simulation, and discrete event simulation are thoroughly discussed, all of which are significant to a complete understanding of modeling and simulation. The book also features chapters that outline sophisticated methodologies, verification and validation, and the importance of interoperability. A related FTP site features color representations of the book's numerous figures. Modeling and Simulation Fundamentals encompasses a comprehensive study of the discipline and is an excellent book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of computational statistics, engineering, and computer science who use statistical modeling techniques.Content: Chapter 1 Introduction to Modeling and Simulation (pages 1–24): Catherine M. BanksChapter 2 Statistical Concepts for Discrete Event Simulation (pages 25–56): Roland R. MielkeChapter 3 Discrete?Event Simulation (pages 57–98): Rafael Diaz and Joshua G. BehrChapter 4 Modeling Continuous Systems (pages 99–130): Wesley N. ColleyChapter 5 Monte Carlo Simulation (pages 131–145): John A. SokolowskiChapter 6 Systems Modeling: Analysis and Operations Research (pages 147–180): Frederic D. McKenzieChapter 7 Visualization (pages 181–225): Yuzhong ShenChapter 8 M&S Methodologies: A Systems Approach to the Social Sciences (pages 227–270): Barry G. Silverman, Gnana K. Bharathy, Benjamin Nye, G. Jiyun Kim, Mark Roddy and Mjumbe PoeChapter 9 Modeling Human Behavior (pages 271–324): Yiannis Papelis and Poornima MadhavanChapter 10 Verification, Validation, and Accreditation (pages 325–372): Mikel D. PettyChapter 11 An Introduction to Distributed Simulation (pages 373–402): Gabriel A. Wainer and Khaldoon Al?ZoubiChapter 12 Interoperability and Composability (pages 403–433): Andreas Tolk