Noa Agmon is an assistant professor at the Computer Science department at Bar-Ilan University (BIU). Her research focuses on multi-robot systems, while using both theoretical and empirical means for evaluation of team performance guarantees on a variety of robotic tasks, for example multi-robot patrol and robot navigation. She received her PhD from Bar-Ilan University (2009), and her MSc from the Weizmann Institute (2004), and spent two years at The University of Texas (UT) at Austin before accepting the faculty position at BIU, where she established and heads the Security Robotics Lab.
Talk: Robotic Strategic Behavior in Adversarial Environments
Robots act in adversarial environments. It is a fact. Unfortunately, little research has been done in the robotics community on strategic robotic behavior considering the existence of an adversary. This talk summarizes recent research achievements in the emerging area of Adversarial Robotics: accounting for adversarial presence in robotic tasks. This will be demonstrated by four different problems: multi-robot patrolling, robotic coverage, robot-team formation, and robot navigation. We have shown that considering an adversary leads to a more general problem, where operating in neutral environments (as has been done so far) is actually an instance of this problem, that assumes a specific (usually simple, random) adversarial model.
Bo An is a Nanyang Assistant Professor with the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst. His current research interests include artificial intelligence, multiagent systems, game theory, and optimization. He has published over 70 referred papers at AAMAS, IJCAI, AAAI, ICAPS, KDD, JAAMAS, AIJ and ACM/IEEE Transactions. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the Best Innovative Application Paper Award at AAMAS-12, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and the Innovative Application Award at IAAI-16. He was invited to give Early Career Spotlight talk at IJCAI-17. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He is a member of the editorial board of JAIR and the Associate Editor of JAAMAS. He was elected to the board of directors of IFAAMAS.
Talk: Recent Progress on Computational Game Theory for Security
Security is a critical concern around the world, whether it’s the challenge of protecting ports, airports and other critical national infrastructure, or protecting wildlife and forests, or suppressing crime in urban areas. In many of these cases, limited security resources prevent full security coverage at all times; instead, these limited resources must be scheduled, avoiding schedule predictability, while simultaneously taking into account different target priorities, the responses of the adversaries to the security posture and potential uncertainty over adversary types. Computational game theory can help design such unpredictable security schedules and new algorithms are now deployed over multiple years in multiple applications for security scheduling. These applications are leading to real-world use-inspired research in computational game theory in scaling up to large-scale problems, handling significant adversarial uncertainty, dealing with bounded rationality of human adversaries, and other interdisciplinary challenges. This talk will discuss some recent research progress on computational game theory for security based on results published at recent AAMAS/AAAI/IJCAI conferences.