Talk: Adversarial Risk Analysis

Of interest in particular, due to the adversarial element.   Risk analysis does not often enough consider the intelligent nature of agents that create risk.   Competitors for example, and now even intelligent agents in the form of assistants or other machine driven systems.

The OBAIS department at the Lindner College of Business, University of Cincinnati, invites you to attend the Lindner Research Excellence Seminar and Professional Development Discussion:

Research Seminar:
Date and time: Friday, April 6, 2018, 10:30AM-12:00PM 
Location: Lindner Hall 218
Speaker: Dr. David Banks, Duke University
Title: Adversarial Risk Analysis

Abstract: Adversarial Risk Analysis (ARA) is a Bayesian alternative to classical game theory. Rooted in decision theory, one builds a model for the decision-making of one's opponent, placing subjective distributions over all unknown quantities. Then one chooses the action that maximizes expected utility. This approach aligns with some perspectives in modern behavioral economics, and enables principled analysis of novel problems, such as a multiparty auction in which there is no common knowledge and different bidders have different opinion about each other.

This presentation is based on:
Rios Insua, D., Rios, J., Banks, D. L., “Adversarial Risk Analysis,” Journal of the American Statistical Association, 2009.
https://www.tandfonline.com/doi/abs/10.1198/jasa.2009.0155
Banks, D. L., Rios, J., Rios Insua, D., “Adversarial Risk Analysis,” Chapman and Hall/CRC, 2015, ISBN 9781498712392.

https://www.crcpress.com/Adversarial-Risk-Analysis/Banks-Aliaga-Insua/p/book/9781498712392

Best wishes,
Yichen Qin,  Assistant Professor
Department of Operations, Business Analytics, and Information Systems
Lindner College of Business, University of Cincinnati
Website: http://business.uc.edu/academics/departments/obais/faculty/qinyn.html
Email: qinyn@ucmail.uc.edu





Biography: Professor David Banks currently serves as the Director of the Statistical and Applied Mathematical Sciences Institute (SAMSI). David Banks has served as the editor-in-chief for the Journal of the American Statistical Association, Applications and Case Studies. He co-founded the journal Statistics and Public Policy and served as its editor. He co-founded the American Statistical Association's Section on National Defense and Homeland Security, and has chaired that section, as well as the sections on Risk Analysis and on Statistical Learning and Data Mining. In 2003 he led a research program on Data Mining at the Statistical and Applied Mathematical Sciences Institute; in 2008, he led a research program at the Isaac Newton Institute on Theory and Methods for Complex, High-Dimensional Data; in 2012, he led another SAMSI research program, on Computational Advertising. He has published 74 refereed articles, edited eight books, and written four monographs.

David Banks is past-president of the Classification Society, and has twice served on the Board of Directors of the American Statistical Association. He is currently the president of the International Society for Business and Industrial Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He recently won the American Statistical Association's Founders Award.

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, forensics, and certain topics in high-dimensional data analysis.