Adversarial Risk Analysis: 1st Edition (Hardback) book cover

Adversarial Risk Analysis

1st Edition

By David L. Banks, Jesus M. Rios Aliaga, David Rios Insua

Chapman and Hall/CRC

224 pages | 42 B/W Illus.

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pub: 2015-06-30
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Description

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 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.

    Reviews

    "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

    Table of Contents

    Games and Decisions

    Game Theory: A Review

    Decision Analysis: An Introduction

    Influence Diagrams

    Problems

    Simultaneous Games

    Discrete Simultaneous Games: The Basics

    Modeling Opponents

    Comparison of ARA Models

    Problems

    Auctions

    Non-Strategic Play

    Minimax Perspectives

    Bayes Nash Equilibrium

    Level-k Thinking

    Mirror Equilibria

    Three Bidders

    Problems

    Sequential Games

    Sequential Games: The Basics

    ARA for Sequential Games

    Case Study: Somali Pirates

    Case Study: La Relance

    Problems

    Variations on Sequential Defend-Attack Games

    The Sequential Defend-Attack Model

    Multiple Attackers

    Multiple Defenders

    Multiple Targets

    Defend-Attack-Defend Games

    Learning

    A Security Case Study

    Casual Fare Evaders

    Collusion

    Pickpockets

    Evaders and Pickpockets

    Multiple Stations

    Terrorism

    Other Issues

    Complex Systems

    Applications

    Solutions to Selected Exercises

    References

    Index

    About the Authors

    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.

    Subject Categories

    BISAC Subject Codes/Headings:
    BUS049000
    BUSINESS & ECONOMICS / Operations Research
    MAT011000
    MATHEMATICS / Game Theory
    MAT029000
    MATHEMATICS / Probability & Statistics / General