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A selective review of modern decision science and implications for decision-support systems. The study suggests ways to synthesize lessons from research on heuristics and biases with those from "naturalistic research." It also discusses modern tools, such as increasingly realistic simulations, multiresolution modeling, and exploratory analysis, which can assist decisionmakers in choosing strategies that are flexible, adaptive, and robust.
A selective review of modern decision science and implications for decision-support systems. The study suggests ways to synthesize lessons from research on heuristics and biases with those from "naturalistic research." It also discusses modern tools, such as increasingly realistic simulations, multiresolution modeling, and exploratory analysis, which can assist decisionmakers in choosing strategies that are flexible, adaptive, and robust.
Based on many years of applied research, modeling and educating future decision makers, the authors have selected the critical set of mathematical modeling skills for decision analysis to include in this book. The book focuses on the model formulation and modeling building skills, as well as the technology to support decision analysis. The authors cover many of the main techniques that have been incorporated into their three-course sequence in mathematical modeling for decision making in the Department of Defense Analysis at the Naval Postgraduate School. The primary objective of this book is illustrative in nature. It begins with an introduction to mathematical modeling and a process for formally thinking about difficult problems, illustrating many scenarios and illustrative examples. The book incorporates the necessary mathematical foundations for solving these problems with military applications and related military processes to reinforce the applied nature of the mathematical modeling process.
An examination of analysis and analysis practices for defense planning, the paper1s purpose is to delineate priorities for the way ahead, i.e., for investments and other actions to ensure that future models and simulations will serve the needs of decisionmakers. The analysis in question is accomplished for Quadrennial Reviews and for continuing work on capability assessments, requirements analysis, and program analysis.
The military is locked in a technology-driven orientation that designed great command and control systems for the Cold War, but this same mentality is inadequate to address decision making challenges of the future. Consequently, the military must rebuild its intellectual framework to link decision makers to forces in an incredibly dynamic environment. The appropriate rebuilding is through a decision-centered approach to command and control systems. To adequately comprehend this approach, policy makers must understand how humans decide and how decision makers fit into complex systems. This study investigates current research on decision making and links naturalistic decision making theory with complexity theory to provide a basis for analyzing decision support systems. Using Boyd's OODA loop as a frame of reference, this paper describes how the post cold war orientation has changed decision requirements. Next, the study proceeds with a discussion on decision theory with thoughts on how recent progress in naturalistic decision making theory should fundamentally redirect decision system design. Complexity theory offers an opportunity to link the decision maker to other elements of a unit and provides a basis for advocating decision-centered methods to improve decision performance. The study concludes with comments and recommendations on current efforts to move toward decision centered design.
Modeling, simulation, and analysis (MS&A) is a crucial tool for military affairs. MS&A is one of the announced pillars of a strategy for transforming the U.S. military. Yet changes in the enterprise of MS&A have not kept pace with the new demands arising from rapid changes in DOD processes and missions or with the rapid changes in the technology available to meet those demands. To help address those concerns, DOD asked the NRC to identify shortcomings in current practice of MS&A and suggest where and how they should be resolved. This report provides an assessment of the changing mission of DOD and environment in which it must operate, an identification of high-level opportunities for MS&A research to address the expanded mission, approaches for improving the interface between MS&A practitioners and decision makers, a discussion of training and continuing education of MS&A practitioners, and an examination of the need for coordinated military science research to support MS&A.
Chaos theory is a poorly understood concept in social science and in military analytical decision making systems. Military decision makers require a multidisciplinary approach of mathematical analysis, modeling and simulation, topology, and post-structural philosophy if they intend to conceptualize chaos theory and complex adaptive systems and theirs relevance to military planning. The essence of this understanding is that while chaos appears random, chaos properly understood is a deterministic series found in very simple forms. These forms exhibit sensitivity to initial conditions, bounding, and attractors. Despite various methods for detecting chaos in mechanical systems, data set size limitations and inability to separate out adaptive behaviors make these techniques of little value in situ. Adaptation and complexity are phenomena that are very different from chaos. Higher order interactions and effects, self-organization, and propensity of co-evolution and novel emergence distinguish chaos from stochastic processes. The self-organization and emergence are evident when a cumulative effect is different from the additive effects of the components. These self-organizing components differ from chaos because the properties of resolution and scope are fundamentally different. The fractal nature of chaos ensures that it is scale less and, therefore, unable to produce novel emergent effects. One way to conceptualize chaos within complexity is through the Deleuzian post-structural Philosophy of Difference regarding Smooth and Striated Spaces and Nomad versus the Sedentary agents. This conceptualization, transferred to chaos applications, links turbulence to barriers and increased gridding on the surface of open systems. These barriers inform agents on suitable terrain and options during decision-making.