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March 2017
Free

CESG Teleseminar: Mixed Centralized/Decentralized Decision Protocols for Multi-Agent Systems

March 2 @ 2:30 pm - 4:00 pm

Abstract Multi-agent systems arise in diverse fields, including power systems, robotics, cyber-physical systems, and the Internet of Things. Coordinating these systems is often done using decentralized interactions, in which each agent only communicates with a small number of others. Decentralized algorithms offer several benefits, though they may have difficulty accommodating some performance demands, such as user privacy requirements. Toward addressing such challenges, I will present recent work on mixed centralized/decentralized decision protocols for multi-agent systems. Motivated by the availability of cloud computing, a centralized cloud computer is added to networks of agents in order to gather global information, perform centralized computations, and broadcast the results. As this happens, the agents continue to execute a decentralized behavior. The centralized nature of the cloud means it will be slower than the agents, though its slow, occasional transmissions do indeed enable multi-agent systems to handle various practical challenges. To this end, I will present mixed centralized/decentralized coordination algorithms that tolerate asynchronous information sharing and user privacy requirements, while still enabling strong theoretical guarantees of performance. In the asynchronous case, I will present an algorithm that allows each agent to perform useful work even if the agents have conflicting information about the network. For privacy, the framework of differential privacy is used, giving rise to a novel stochastic optimization algorithm. These algorithms draw from primal-dual optimization techniques and the theory of stochastic variational inequalities, and solve coordination tasks that are stated as convex optimization problems. The end result is a flexible coordination framework that tolerates an array of practical challenges, all while solving constrained coordination problems for teams of agents, regardless of whether an agent is a robot, a self-driving car, or any other physical entity. In addition to theoretical results, I will present robotic implementations of this work to demonstrate its applicability in practice. Bio Matthew Hale is a Ph.D. Candidate in Electrical and Computer Engineering at the Georgia Institute of Technology. In 2012, he received his B.S.E. in Electrical Engineering from the University of Pennsylvania, where he was a member of the GRASP Lab. He received his M.S. in Electrical and Computer Engineering from Georgia Tech in 2015, and was awarded the Colonel Oscar P. Cleaver Outstanding Graduate Student Award by the same department in 2013. His research interests include optimization and control for multi-agent systems, differential privacy, and hybrid systems. His work applies methods from these areas to cyber-physical systems and teams of robots.

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Free

CESG Teleseminar: Improving Cyber Security through Cyber Insurance and Data Analytics

March 3 @ 4:10 pm - 5:10 pm
WEB, Room 236-C,
Wisenbaker Engineering Building
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Parinaz Naghizadeh, University of Michigan Attempts to improve the state of cyber security have been on the rise over the past decade. In addition to enhancing existing software and infrastructure, there is a parallel need for incentivizing the adoption of these improved security practices by end users and organizations. My research aims to design such incentive mechanisms, and to leverage advances in data analytics for informed cyber-policy design. In this talk, I will first discuss the design of cyber insurance contracts, with an emphasis on users’ unobservable security decisions (moral hazard) and their interdependence in security. I will demonstrate the role of cyber insurance in instilling commitment towards improved cyber security by leveraging users’ interdependence. In addition, I will describe how predictive analytics based on machine learning techniques can be used as a tool for improving the design of these cyber-insurance contracts, and also for regulating security information sharing agreements. Further, I will present a game-theoretic framework for understanding individual users’ decisions towards security investments, and in particular, the effects of the network structure on the outcomes of their interactions. I will discuss how our findings extend several existing results in the literature, as well as their applications in other domains, including the study of spread of research and innovation, financial markets, and environmental pollution reduction policies. Bio: Parinaz Naghizadeh is a postdoctoral research fellow in EECS at the University of Michigan. Her research interests include cyber security, game theory, network economics, optimization, and data analytics. She received her Ph.D. in electrical engineering from the University of Michigan in 2016, M.Sc. degrees in electrical engineering and mathematics, both from the University of Michigan, in 2013 and 2014, respectively, and a B.Sc. in electrical engineering from Sharif University of Technology, Iran, in 2010. She was a recipient of the Barbour scholarship in the 2014-15 academic year.

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Free

ECE Leaders and Innovators Speaker Series and TEES Tech Talk

March 10 @ 11:30 am - 12:30 pm
WEB, Room 236-C,
Wisenbaker Engineering Building

New Frontiers of Information Networks: Opportunities & Challenges Dr. John D. Matyjas Air Force Research Laboratory Information Directorate Abstract: After a brief orientation on the Air Force Research Laboratory, this talk will focus on the innovation, development, and maturation of secure communications,  networking, and information management technologies. A timely, reliable, and mission-responsive Air Force network is critical to the translation of sensory data into actionable information and for assuring tailored communications globally. To build future elastic network capabilities that can respond to the mission and threat environment, we cannot rely solely on a data-neutral network. The future lies in affordable, extensible, interoperable communications architectures that intelligently distribute information in a robust way and enable shared situational awareness and timely decision-making, ultimately, to assure the mission. These desired attributes will be discussed in the context of broadly parallel consumer and industry demands for autonomous vehicle (ground and airborne) operations and human/machine-to-machine communications. Bio: Dr. John D. Matyjas received his Ph.D. in electrical engineering from State University of New York at Buffalo in 2004. Currently, he is serving as the Tech Advisor of the Computing & Communications Division at the Air Force Research Laboratory (AFRL) in Rome, NY. His research interests include dynamic multiple-access communications and networking, software defined RF, spectrum mutability, statistical signal processing and optimization, and neural networks. Dr. Matyjas was inducted as an AFRL Fellow in 2016. He is the recipient of the 2015 Air Force Association ‘Technology Manager of the Year’ Award, 2015 AFRL ‘Scientist of the Year’ Award, 2012 IEEE R1 Technology Innovation Award, and the 2010 IEEE Int’l Communications Conf. Best Paper Award. From 2012-2014, he served on the IEEE Trans. on Wireless Communications Editorial Advisory Board. He is an IEEE Senior Member, Secretary of the IEEE Mohawk Valley Section, chair of the IEEE Mohawk Valley Signal Processing Society, and member of Tau Beta Pi and Eta Kappa Nu Engineering Honor Societies.

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