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AIC Seminar Series

Towards Practical Heterogeneous Teams

Paul ScerriCarnegie Mellon University

Notice:  hosted by Regis Vincent

Date:  1957-05-11 at 11:00

Location:  EJ228  (Directions)

   Abstract

The process of taking well developed theories of teamwork and creating large, practical, heterogeneous teams has revealed new challenges requiring novel solutions. In this talk, I will discuss some of the challenges and the solutions we have developed. Specifically, I will focus on the use of *tokens* as an abstraction for scalable and robust coordination algorithms. Tokens encapsulate both information and control, thus allowing agents to make local decisions that are likely to lead to good global behavior. A key to many of our scalable coordination algorithms is that locally improbable events become highly likely on a large scale. These algorithms often use orders of magnitude less communication than optimal approaches while performing almost as well. I will also discuss some of the additional algorithms, e.g., meta-reasoning, that are useful for practical environments. Finally, I will describe applications of the approach to a variety of projects and open issues raised by specific projects.

   Bio for Paul Scerri

Paul Scerri is a Systems Scientist at Carnegie Mellon University. Since 1997, when his RoboCup football simulation team won a game at the first world championships, Paul has been dedicated to building bigger and better teams (because his team also lost two games and he is very competitive). Currently, much of his focus is on heterogeneous teams with a mixture of robots, agents and people. His thesis work, conducted at Linkoping University and USC, and post-doctoral work at USC, looked specifically at how humans and agents can flexibly work together, transferring control in a way that maximizes overall team reward. Since then, he has been trying to make bigger and bigger teams for a variety of domains. Most recently Paul has been building heterogeneous teams of unmanned aerial vehicles which isn’t half as much fun as RoboCup soccer, but uses many of the same algorithms and makes for some really cool demos.

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