PhD Defense: "Exploiting Stochasticity in Multi-agent Systems"

Alexandre R Mesquita

November 30th (Tuesday), 3:30pm
Engineering Science Building (ESB), Rm 2001

Some of the main challenges in multi-agent systems arise from the fact that agents only have access to local information or to information that is exchanged using faulty communication networks. In this talk, we discuss two multi-agent applications in which these issues are present.

In the first application, stochasticity is introduced to overcome uncertainty about the environment. Inspired by bacterial chemotaxis, we design algorithms that control the spatial distribution of mobile agents that can take point measurements of a monitored function but cannot measure their own positions. Applications include source-seeking, environmental monitoring and deployment. We prove that the probability density of agents is led to converge exponentially to a predetermined function of the measurements, much like in Markov Chain Monte Carlo methods.

In the second application, the level of stochasticity in a networked control system is regarded as a control variable. We show that, by judiciously transmitting redundant copies of the same data in a faulty network, we obtain significant performance gains with only a modest increase in the total number of transmissions. We develop techniques to design communication protocols that exploit redundant transmissions, while seeking a balance between stability/estimation performance and communication rate.

About Alexandre R Mesquita:

Alexandre R. Mesquita received his BSc and MSc degrees in Electronics Engineering in 2004 and 2006, respectively, from the Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, Brazil. He is currently a PhD candidate at the University of California, Santa Barbara. His research interests include multi-agent systems, networked control systems, stochastic hybrid systems and stochasticity in biology.

Hosted by: Professor Joao Hespanha