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Challenges in Computational Social Modeling and Simulation for National Security Decision Making

机译:国家安全决策的计算社会建模与仿真面临的挑战

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On October 26th and 27th, 2010, Sandia National Laboratories (SNL) organized an interdisciplinary workshop in which participants from a range of institutions and research backgrounds presented and discussed papers on a range of topics related to the development and use of computational social science (CSS) in national security decision-making. Computational social science refers to the use of computational modeling and simulation approaches, including agent- based, social network, discrete event, and systems dynamics methodologies, to study behavioral, cultural, and social dynamics. CSS has long roots in computer science, artificial intelligence, and quantitative social science. Over the past decade, CSS methods have captured the attention of the national security community as a source of analytic and decision-support technologies for a range of challenges, from counterinsurgency to terrorism. The first phase of this project was a comparative, interdisciplinary review of literature related to applied computational modeling and simulation in both the social and physical sciences; this study is described in a summary paper that McNamara and Trucano authored (Appendix A). The workshop participants reviewed the work by McNamara and Trucano in light of their own research and work experiences. Our participants included social, computational, and physical scientists from a range of government, industry, and academic institutions. Most, but not all, had also participated in projects to develop and deploy computational models and simulations of social phenomena for decision-making; and over half the participants had worked on computational modeling and simulation projects in national security contexts.

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