Addressing Real-world Societal Challenges:
Advanced Game-Theoretic Models and Algorithms

Dr. Thanh H. Nguyen, University of Michigan

1:15-2:15 Thursday, 29 March 2018, ITE 325, UMBC

This talk will cover my research in AI, with a focus on Multi-Agent Systems, for solving real-world societal problems, particularly in the areas of Sustainability, Public Safety and Security, Cybersecurity, and Public Health. In these problems, strategic allocation of limited resources in an adversarial environment is an important challenge which involves complex human decision making, a variety of uncertainties, and exponential action spaces. I will present my research in developing advanced game-theoretic models and algorithms for tactical allocation decisions in these problems. In particular, I will outline three main contributions of my research: (i) learning new behavioral models of human decision-making for adversarial reasoning – I will discuss results from applying these models to both human subjects data from the lab and real-world data; (ii) developing robust game-theoretic algorithms, which handle a variety of uncertainties in security and are applied to domains in which data is not available to generate a prior distribution of uncertainties; and (iii) designing scalable game-theoretic algorithms, which address the challenge of exponential action and state spaces in complex cybersecurity problems. Finally, I will briefly introduce the real-world deployed application PAWS (Protection Assistant for Wildlife Security), which incorporates my models and algorithms, for wildlife protection.

Thanh Nguyen is a Postdoctoral Researcher in the Department of Computer Science & Engineering at the University of Michigan. She received her Ph.D. from the Department of Computer Science at the University of Southern California (USC) in Summer 2016. While at USC, she was part of the USC Center for Artificial Intelligence in Society. Her work in the area of Artificial Intelligence is motivated by real-world societal problems, particularly in the areas of Sustainability, Public Safety and Security, Cybersecurity, and Public Health. Her recent awards include the Deployed Application Award (IAAI 2016) and Runner-up of the Best Innovative Application Paper Award (AAMAS 2016). Thanh has published extensively in several leading conferences in Artificial Intelligence, including IJCAI, AAAI, AAMAS, and GameSec. She has contributed to build the real-world wildlife-protection application PAWS (Protection Assistant for Wildlife Security), which has been extensively used by NGOs in conservation areas in multiple countries.