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Adversarial risk analysis

By: Banks, David L.
Contributor(s): Rios, Jesus | Ríos Insua, David.
Publisher: Boca Raton CRC Press 2016Description: x, 214 p.ISBN: 9781498712392.Subject(s): Game theory | Risk assessmentDDC classification: 519.3 Summary: 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. 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 opponent’s 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. (https://www.crcpress.com/Adversarial-Risk-Analysis/Banks-Aliaga-Rios-Insua/9781498712392)
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Item type Current location Item location Collection Call number Status Date due Barcode
Books Vikram Sarabhai Library
Slot 1407 (0 Floor, East Wing) Non-fiction 519.3 B2A2 (Browse shelf) Available 190509

Table of Contents:

1. Games and Decisions
2. Simultaneous Games
3. Auctions
4. Sequential Games
5. Variations on Sequential Defend-Attack Games
6. A Security Case Study
7. Other Issues

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.
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 opponent’s 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.

(https://www.crcpress.com/Adversarial-Risk-Analysis/Banks-Aliaga-Rios-Insua/9781498712392)

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