David Banks, Duke University

Abstract

Adversarial Risk Analysis (ARA) is a decision-theoretic alternative to game theory, applicable to corporate competition, auctions, and counterterrorism. In ARA, one builds a model for the strategic decision making of one's opponent(s), and then places subjective Bayesian distributions over unknown quantities. This structure enables the analyst to compartmentalize distinct kinds of uncertainty. Within this framework one can use standard Bayesian techniques to develop a probability distribution over the actions of the opponent. Given this distribution, the decision theorist chooses the action that maximizes expected utility.

Speaker Bio: David Banks is director of the Statistical and Applied Mathematical Sciences Institute (SAMSI) and Professor of the Practice in Statistical Science at Duke University. His research areas include models for dynamic networks, dynamic text networks, adversarial risk analysis (i.e., Bayesian behavioral game theory), human rights statistics, agent-based models, and forensics, as well as selected topics in high-dimensional data analysis. He is a Fellow of the Institute of Mathematical Statistics and of the American Statistical Association (ASA) and 2015 recipient of the ASA’s Founder’s Award. Banks is past-president of the Classification Society and has twice served on ASA’s Board of Directors. His book, Adversarial Risk Analysis, with David Ríos Insua and Jesus Rios, won the 2018 DeGroot Award. Banks was co-organizer of several DIMACS workshops, including the 2010 workshop on Adversarial Decision Making, and a leader in the DIMACS Special Focus on Computational and Mathematical Epidemiology.

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