Adversarial Risk Analysis - Banks, David L.; Rios Aliaga, Jesus M.; Rios Insua, David
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This book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. A case study based on a real application in railway security provides a blueprint for how to perform ARA in similar security situations. In addition, multi-agent influence diagrams help readers visualize complex information structures.

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Produktbeschreibung
This book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. A case study based on a real application in railway security provides a blueprint for how to perform ARA in similar security situations. In addition, multi-agent influence diagrams help readers visualize complex information structures.
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Autorenporträt
David L. Banks is a professor in the Department of Statistical Science at Duke University. His research interests include data mining and risk analysis. Jesus Rios is a researcher in risk and decision analytics for the Cognitive Computing Department at the IBM Research Division. His research focuses on applying risk and decision analysis to solve complex business problems. David Ríos Insua is the AXA-ICMAT Chair in Adversarial Risk Analysis at the Institute of Mathematical Sciences ICMAT-CSIC and a member of the Spanish Royal Academy of Sciences. His research interests include risk analysis, decision analysis, Bayesian statistics, security, aviation safety, and social robotics.
Rezensionen
"This well-written and concise text is an introduction to the field of adversarial risk analysis (ARA), which is a form of decision and risk analysis which incorporates uncertainty and game theory to model strategies of an adversary...There is an appropriate amount of detail throughout the book, making it suitable for a reference text as well as a book which may be read cover to cover and it is both thought provoking and enlightening."
-Matthew Craven, Plymouth University, Journal of the Royal Statistical Society, Series A, January 2017

"Here, Banks (Duke Univ.), Rios (IBM), and Insua (ICMAT-CSIC, Spain) identify three categories of uncertainty for the strategist: aleatory uncertainty-nondeterminism of outcomes even after players make choices; epistemic uncertainty-hidden information concerning opponents' preferences, beliefs, and capabilities; and concept uncertainty-hidden information concerning opponents' strategies. Adversarial risk analysis, a new field with roots in modern efforts to defeat terrorism, provides a framework, in principle, to cope with these uncertainties. Solving the models seems generally intractable, but the heart of the book, the first of its kind, offers exemplary case studies. Summing up: Recommended. Lower-division undergraduates and above; informed general audiences."
-D. V. Feldman, University of New Hampshire, Durham, USA, for CHOICE, March 2016