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Teamwork Planning and Learning in Adversarial Multi-Robot Domains

  • Manuela Veloso

Abstract

We have been participating in the RoboCup robot soccer small-size league for more than ten years. Such multi-robot domain offers a variety of challenges, including perception, control, actuation, and teamwork. In this talk, I will present an overview of the advances we have made along these years, namely in efficient vision processing, in physics-based motion planning, in adapting to the opponent, and in coordination and teamwork. At the end, I will outline the directions of our current work, in particular in building large teams of small robots, and analyzing and learning from data logged from the robots fast execution.

Keywords

Multiagent System Autonomous Agent President Elect Analogical Reasoning Computer Science Department 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Computer Science Department School of Computer ScienceCarnegie Mellon UniversityPittsburghUSA

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