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https://doi.org/10.1109/robot....
Article . 2004 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.1184/r1/...
Other literature type . 2003
Data sources: Datacite
https://dx.doi.org/10.1184/r1/...
Other literature type . 2003
Data sources: Datacite
DBLP
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Multi-robot team response to a multi-robot opponent team

Authors: James Bruce; Michael H. Bowling; Brett Browning; Manuela M. Veloso;

Multi-robot team response to a multi-robot opponent team

Abstract

Adversarial multi-robot problems, where teams of robots compete with one another, require the development of approaches that span all levels of control and integrate algorithms ranging from low-level robot motion control, through to planning, opponent modeling, and multiagent learning. Smallsize robot soccer, a league within the RoboCup initiative, is a prime example of this multi-robot team adversarial environment. In this paper, we describe some of the algorithms and approaches of our robot soccer team, CMDragons’02, developed for RoboCup 2002. Our team represents an integration of many components, several of which that are in themselves state-of-theart, into a framework designed for fast adaptation and response to the changing environment.

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Keywords

FOS: Computer and information sciences, 80101 Adaptive Agents and Intelligent Robotics

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    popularity
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    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Average
Top 10%
Top 10%