Adversarial Risk Analysis (Overview)

TL;DR

Adversarial Risk Analysis (ARA) is a Bayesian framework for decision-making against intelligent opponents, modeling uncertainties about their utilities and strategies to optimize outcomes.

Contribution

This paper provides a comprehensive overview of ARA, including its conceptual foundations, modeling techniques, computational methods, and applications.

Findings

ARA enables modeling of opponent utilities and strategies.

It produces probability distributions over opponents' actions.

The overview discusses practical and theoretical challenges.

Abstract

Adversarial risk analysis (ARA) is a relatively new area of research that informs decision-making when facing intelligent opponents and uncertain outcomes. It enables an analyst to express her Bayesian beliefs about an opponent's utilities, capabilities, probabilities and the type of strategic calculation that the opponent is using. Within that framework, the analyst then solves 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 that permits the analyst to maximize her expected utility. This overview covers conceptual, modeling, computational and applied issues in ARA.