AI and Multiagent Systems for Safety and Security
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Speaker (s):
Arunesh Sinha
Assistant Research Scientist,
Computer Science and Engineering Department,
University of Michigan
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Date:
Time:
Venue:
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January 21, 2019, Monday
10:00am - 11:00am
Meeting Room 5.1, Level 5
School of Information Systems
Singapore Management University
80 Stamford Road
Singapore 178902
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ABSTRACT
Understanding the complex defender-adversary interaction in any adversarial interaction allows for the design of intelligent and adaptive defense. Game theory is a natural model for such multi-agent interaction. However, significant challenges need to be overcome in order to apply game theory in practice. In this talk, I will present my work on addressing two such challenges: scalability and learning opponent behavior in games. First, I will present a game model of screening of passengers at airports and a novel optimization approach based on randomized allocation and disjunctive programming techniques to solve large instances of the problem. This airport screening work was done in collaboration with the Transport Security Administration in USA. Next, I will present shortcomings of learning adversary behavior and planning optimal defensive actions based on the learned model. A formal learning theory analysis of the learning module reveals why such learning and planning composition fails. I will also present a technique to fix this problem in a security game setting. This emphasizes the need of formal compositional reasoning when using learning as a component in large multi-agent systems.
About the Speaker
Dr. Arunesh Sinha is an Assistant Research Scientist in the Computer Science Department at the University of Michigan. He was a postdoctoral scholar with Prof. Milind Tambe at the University of Southern California. He received his Ph.D. from Carnegie Mellon University, where he was advised by Prof. Anupam Datta. He obtained his undergraduate degree in Electrical Engineering from IIT Kharagpur in India. He worked as a software engineer before starting his Ph.D. He has industry research experience in the form of internships at Microsoft Research, Redmond and Intel Labs, Hillsboro. He was awarded the Bertucci fellowship at CMU in appreciation of his novel research. His paper was nominated for the best innovative application paper in AAMAS 2016. Dr. Sinha has conducted research at the intersection of security, machine learning and game theory. His interests lie in the theoretical aspects of multi-agent interaction, machine learning, security and privacy, along with an emphasis on the real-world applicability of the theoretical models.
