FRC Seminar Special Time:Information Sharing in Large Heterogeneous Teams, August 13, 2009

FRC Seminar

August 13, 2009 12pm

Speaker:

Prasanna Velagapudi
PhD Student
Robotics Institute
Carnegie Mellon University

Abstract:

In large, collaborative, heterogeneous teams, team members often collect information that is useful to other members of the team. However, in many real domains, it is impossible to completely share all of this information due to network and processing constraints. Recognizing the utility of such information and delivering it efficiently across a team has been the focus of much research, with proposed approaches ranging from flooding to complex filters and matchmakers. Interestingly, random forwarding of information has been found to be a surprisingly effective information sharing approach in some domains. In this talk, we investigate some recent results supporting this phenomenon in detail and show that in certain systems, random forwarding of information performs almost half as well as a globally optimal approach. From this, we demonstrate a statistical modeling approach designed to estimate information sharing performance in real domains. Finally, we will discuss ongoing work and possible applications of these models in enabling heterogeneous teams to be scaled into the 100s and 1000s.

Speaker Bio:

Prasanna is currently pursuing a PhD at the Robotics Institute, and is co-advised by Katia Sycara and Paul Scerri. His research focuses on information sharing in large heterogeneous teams and large-scale human-robot interaction. Previously, he worked as an electrical engineer at RedZone Robotics, developing on power systems and embedded computing for submersible, subterranean mapping and mobility applications. Prasanna holds a B.S. in Electrical and Computer Engineering and Computer Science from Carnegie Mellon University.