University of California, Riverside

Department of Electrical and Computer Engineering



Distinguished Colloquium Speaker: Professor Ali H. Sayed presents a talk on "Adaptation and Learning by Networked Agents"


Distinguished Colloquium Speaker: Professor Ali H. Sayed presents a talk on....
 
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Distinguished Colloquium Speaker: Professor Ali H. Sayed presents a talk on "Adaptation and Learning by Networked Agents"

April 10, 2017 - 11:10 am
Winston Chung Hall, 205/206

ABSTRACT

Network science deals with issues related to the aggregation, processing, and diffusion of information over graphs. While interactions among agents can be studied from the perspective of cluster formations, degrees of connectivity, and small-world effects, it is the possibility of having agents interact dynamically with each other, and influence each other's behavior, that opens up a plethora of notable possibilities and challenges. For example, examination of how local interactions influence global behavior can lead to a broader understanding of how localized interactions in the social sciences, life sciences, and system sciences influence the evolution of the respective multi-agent networks. In this presentation, we examine the learning behavior of adaptive networked agents over both strongly and weakly-connected graphs. The discussion will reveal some interesting patterns of behavior on how information flows over graphs. In the strongly-connected case, all agents are able to learn the desired true state within the same accuracy level, thus attaining a level of “social equilibrium,” even when the agents are subjected to different noise conditions. In contrast, in the weakly-connected case, a leader-follower relationship develops with some agents dictating the behavior of other agents regardless of the local information clues that are sensed by these other agents. The findings clarify how asymmetries in the exchange of data over graphs can make some agents dependent on other agents. This scenario arises, for example, from intruder attacks by malicious agents, from the presence of stubborn agents, or from failures by critical links. The results have useful implications for the design and operation of multi-agent systems and robotic swarms.

BIOGRAPHY

Ali H. Sayed is a distinguished professor and former chairman of electrical engineering at UCLA, where he leads the UCLA Adaptive Systems Laboratory (www.ee.ucla.edu/asl). An author of over 480 publications and six books, his research involves several areas including adaptation and learning theories, statistical inference, network and data science, multi-agent systems, and biologically-inspired designs. His work has been recognized with several awards including the 2015 Education Award from the IEEE Signal Processing Society, the 2014 Papoulis Award from the European Association for Signal Processing, the 2013 Meritorious Service Award and the 2012 Technical Achievement Award from the IEEE Signal Processing Society, the 2005 Terman Award from the American Society for Engineering Education, and the 2003 Kuwait Prize in Basic Sciences. He has been awarded several Best Paper Awards from the IEEE, and is a Fellow of both the IEEE and the American Association for the Advancement of Science (AAAS). He is recognized as a Highly Cited Researcher by Thomson Reuters. He is currently serving as President-Elect of the IEEE Signal Processing Society during the two-year period 2016-2017, followed as President during 2018-2019.

 

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University of California, Riverside
900 University Ave.
Riverside, CA 92521
Tel: (951) 827-1012

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Electrical and Computer Engineering
Suite 343 Winston Chung Hall
University of California, Riverside
Riverside, CA 92521-0429

Tel: (951) 827-2484
Fax: (951) 827-2425
E-mail: E-mail/Questions

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