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Adversarial Risk Analysis

Name: Adversarial Risk Analysis
Brand: Taylor & Francis Inc
SKU: 09395969
Price: 136.74 EUR
Availability: InStock
Author: David Rios Insua
ISBN: 9781498712392

David Rios Insua

Language

English

Book Hardback

Libristo code: 09395969

Publishers Taylor & Francis Inc, June 2015

Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A... Full description

Libristo code: 09395969

333 b

136.74 €

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Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)

A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations.

Focuses on the recent subfield of decision analysis, ARA

Compares ideas from decision theory and game theory

Uses multi-agent influence diagrams (MAIDs) throughout to help readers visualize complex information structures

Applies the ARA approach to simultaneous games, auctions, sequential games, and defend-attack games

Contains an extended case study based on a real application in railway security, which provides a blueprint for how to perform ARA in similar security situations

Includes exercises at the end of most chapters, with selected solutions at the back of the book

The 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. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponents goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on all unknown quantities. This produces a distribution over the actions of the opponent and enables analysts to maximize their expected utilities.