Imperial College London > Talks@ee.imperial > COMMSP Seminar > Structural Results in Networked Sensor Management

Structural Results in Networked Sensor Management

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This seminar deals with sensor activation and social learning in sensor networks using game theoretic and stochastic control methods.The talk comprises of three parts. In the first part, we describe how social learning leads to rational herding and how optimized social learning has a threshold structure on the simplex of Bayesian posterior distributions. In the second part of the talk, we illustrate how the theory of global games gives a powerful method for designing decentralized data-aware sensor activation algorithms in dense sensor networks. We show that the Nash equilibrium of the sensor network has a simple threshold structure and exhibits a remarkable phase transition as more data is collected. In the third part of the talk we describe how decentralized adaptive filtering algorithms with regret matching can be deployed in sensor networks to guide network behavior to a correlated equilibrium. The convergence analysis of the algorithm involves use of the so called martingale problem and differential inclusions. A major theme of the talk will be the focus on structural properties and convergence analysis that result in numerically efficient algorithms rather than brute force computational methods.

Biography: Vikram Krishnamurthy received his Ph.D from the Australian National University, Canberra, in 1992. He currently is a professor and Canada Research Chair at the Department of Electrical Engineering, University of British Columbia, Vancouver, Canada. His current research interests include computational game theory and stochastic control in sensor networks, and stochastic dynamical systems for modeling of biological ion channels and biosensors. In 2009-2010, he serves as Distinguished lecturer for the IEEE signal processing society. He also serves as editor in chief of IEEE journals selected topics in Signal Processing.

This talk is part of the COMMSP Seminar series.

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