"Combat Modeling" is a systematic learning resource and reference text for the quantitative analysis of combat. After a brief overview, authors Washburn and Kress present individual chapters on shooting without feedback; shooting with feedback; target defense; attrition models; game theory and wargames; search; unmanned aerial vehicles; and terror and insurgency. Three appendices provide a review of basic probability concepts, probability distributions, and Markov models; an introduction to optimization models; and a discussion of Monte-Carlo simulations. Drawing on their many years of experience at the Naval Postgraduate School in Monterey, California, Washburn and Kress have created a reference that will provide the tools and techniques for analysts involved in the underpinnings of combat decisions. This is a book that can be used as a military manual, reference book, and textbook for military courses on this vital subject.

Explore the military and combat applications of modeling and simulation Engineering Principles of Combat Modeling and Distributed Simulation is the first book of its kind to address the three perspectives that simulation engineers must master for successful military and defense related modeling: the operational view (what needs to be modeled); the conceptual view (how to do combat modeling); and the technical view (how to conduct distributed simulation). Through methods from the fields of operations research, computer science, and engineering, readers are guided through the history, current training practices, and modern methodology related to combat modeling and distributed simulation systems. Comprised of contributions from leading international researchers and practitioners, this book provides a comprehensive overview of the engineering principles and state-of-the-art methods needed to address the many facets of combat modeling and distributed simulation and features the following four sections: Foundations introduces relevant topics and recommended practices, providing the needed basis for understanding the challenges associated with combat modeling and distributed simulation. Combat Modeling focuses on the challenges in human, social, cultural, and behavioral modeling such as the core processes of "move, shoot, look, and communicate" within a synthetic environment and also equips readers with the knowledge to fully understand the related concepts and limitations. Distributed Simulation introduces the main challenges of advanced distributed simulation, outlines the basics of validation and verification, and exhibits how these systems can support the operational environment of the warfighter. Advanced Topics highlights new and developing special topic areas, including mathematical applications fo combat modeling; combat modeling with high-level architecture and base object models; and virtual and interactive digital worlds. Featuring practical examples and applications relevant to industrial and government audiences, Engineering Principles of Combat Modeling and Distributed Simulation is an excellent resource for researchers and practitioners in the fields of operations research, military modeling, simulation, and computer science. Extensively classroom tested, the book is also ideal for courses on modeling and simulation; systems engineering; and combat modeling at the graduate level.

"Combat Modeling" is a systematic learning resource and reference text for the quantitative analysis of combat. After a brief overview, authors Washburn and Kress present individual chapters on shooting without feedback; shooting with feedback; target defense; attrition models; game theory and wargames; search; unmanned aerial vehicles; and terror and insurgency. Three appendices provide a review of basic probability concepts, probability distributions, and Markov models; an introduction to optimization models; and a discussion of Monte-Carlo simulations. Drawing on their many years of experience at the Naval Postgraduate School in Monterey, California, Washburn and Kress have created a reference that will provide the tools and techniques for analysts involved in the underpinnings of combat decisions. This is a book that can be used as a military manual, reference book, and textbook for military courses on this vital subject.

The primary goal of this book is to assist the student to develop the skills necessary to effectively employ the ideas of mathematics to solve military problems. At the simplest level I seek to promote an understanding of why mathematics is useful as a language for characterizing the interaction and relationships among quantifiable concepts, or in mathematical terms, variables. The text explores models of terrorism, attrition, search, detection, missile defense, radar, and operational reliability Throughout the text I emphasize the notion of added value and why it is the driving force behind military mathematical modeling. For a given mathematical model to be deemed a success something must be learned that was not obvious without the modeling procedure. Very often added value comes in the form of a prediction. In the absence of added value the modeling procedure becomes an exercise not unrelated to digging a ditch simply to fill it back up again.

Military conflicts, particularly land combat, possess thecharacteristics of complex adaptive systems: combat forces arecomposed of a large number of nonlinearly interacting parts and areorganized in a dynamic command-and-control network; local action, which often appears disordered, self-organizes into long-range order;military conflicts, by their nature, proceed far from equilibrium;military forces adapt to a changing combat environment; and there isno master voice that dictates the actions of every soldier (i

This Note examines the differences in combat outcomes predicted by models of different resolution applied to identical combat situations. First, hypothetical combat situations are posed, then several models of varying degrees of resolution in the spatial representation, aggregation of forces, and time step are used to predict losses and battle winners. Both stochastic and deterministic simulations are used. Comparison of outcomes provides important insights into the problems of aggregation. Observations from this set of experiments are as follows. Intuition regarding outcomes, causes, and effects is frequently wrong, leading to bad approximations in the aggregate. Scaling for different levels of resolution is possible, but a method of predicting the appropriate scaling technique and factors has not been found. The differences in outcomes between stochastic and deterministic models are most pronounced in the 'fair-fight' regime, in which the force balance (accounting for situational factors) is almost even. Because defense analysis frequently operates in this regime (getting just enough force to a theater or because constrained defense budget allocations may not permit overwhelming odds), this implies that great care should be taken to understand the possible variance in outcomes.

Learn how to build, modify, detail, paint and weather legendary aircraft from the experts found in FineScale Modeler magazine. The 18 projects feature classic Allied and Axis that include Gabby's Last Jug, a D-Day Spitfire, an American Mosquito, and a late-war Messerschmitt Bf 109.