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Titlebook: Computational Red Teaming; Risk Analytics of Bi Hussein A. Abbass Book 2015 Springer International Publishing Switzerland 2015 Architecture

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发表于 2025-3-21 18:08:57 | 显示全部楼层 |阅读模式
书目名称Computational Red Teaming
副标题Risk Analytics of Bi
编辑Hussein A. Abbass
视频video
概述Presents first comprehensive treatment of Computational Red Teaming.Provides balanced coverage of the topic from the perspectives of risk thinking and computational modeling.Includes thorough coverage
图书封面Titlebook: Computational Red Teaming; Risk Analytics of Bi Hussein A. Abbass Book 2015 Springer International Publishing Switzerland 2015 Architecture
描述.Written to bridge the information needs of management and computational scientists, this book presents the first comprehensive treatment of Computational Red Teaming (CRT).  The author describes an analytics environment that blends human reasoning and computational modeling to design risk-aware and evidence-based smart decision making systems. He presents the Shadow CRT Machine, which shadows the operations of an actual system to think with decision makers, challenge threats, and design remedies. This is the first book to generalize red teaming (RT) outside the military and security domains and it offers coverage of RT principles, practical and ethical guidelines. .The author utilizes Gilbert’s principles for introducing a science. Simplicity: where the book follows a special style to make it accessible to a wide range of  readers. Coherence:  where only necessary elements from experimentation, optimization, simulation, data mining, big data, cognitive information processing, and system thinking are blended together systematically to present CRT as the science of Risk Analytics and Challenge Analytics. Utility: where the author draws on a wide range of examples, ranging from job i
出版日期Book 2015
关键词Architecture; Big Data; Computational Intelligence; Computational Red Teaming; Data Mining; Observe-Proje
版次1
doihttps://doi.org/10.1007/978-3-319-08281-3
isbn_softcover978-3-319-38441-2
isbn_ebook978-3-319-08281-3
copyrightSpringer International Publishing Switzerland 2015
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Quantitative Practice-Based Researchlenging the effectiveness of a strategic plan or the scalability of an optimization or big-data mining algorithm, the concept of a challenge has the same fundamental characteristics. The purpose of this chapter is to develop a disciplinary approach to structure and model the analysis of risk and the
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https://doi.org/10.1007/978-3-658-01171-0nd big data before presenting the intelligent architectures that can transform data to decisions in CRT systems. Most of these architectures can be used outside CRT in any situation. However, augmenting these architectures with CRT capabilities offers unprecedented computational capabilities for off
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Bart-Jan van Putten,Markus Schieftic manner that is easy to manage. Scenarios as a mean to capture complex plausible futures are discussed, followed by the presentation of guidelines on designing scenarios for CRT exercises. Organizations are complex entities. As such, one section is dedicated to discussing the complexity resulting
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Sleep and Stress: Opposite Conceptsed, where CRT is used to evaluate three conflict-detection algorithms in the domain of air-traffic management (ATM). The second case study presents a lab-based experiment using a game between humans and computers. The objective of the experiment is to test the impact of noise in the information pres
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https://doi.org/10.1007/978-3-319-08281-3Architecture; Big Data; Computational Intelligence; Computational Red Teaming; Data Mining; Observe-Proje
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