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• By Date • By Publication Type • By Research Category • By Author (Currently at CMU) • By Author (Past and Current CORAL Contributors) •
Patrick Riley and Manuela Veloso. On Behavior Classification in Adversarial Environments. In Lynne E. Parker, George Bekey, and Jacob Barhen, editors, Distributed Autonomous Robotic Systems 4, pp. 371–380, Springer-Verlag, 2000.
[PDF]165.7kB [gzipped postscript]40.5kB
In order for robotic systems to be successful in domains with other agents possibly interfering with the accomplishing of goals, the agents must be able to adapt to the opponents' behavior. The more quickly the agents can respond to a new situation, the better they will perform. We present an approach to doing adaptation which relies on classification of the current adversary into predefined adversary classes. For feature extraction, we present a windowing technique to abstract useful but not overly complicated features. In order to take into account the spatial locality of topological differences, we use a previously developed similarity metric. The feature extraction and classification steps are fully implemented in the domain of simulated robotic soccer, and experimental results are presented.
@InCollection{DARS-AdvClass,
author = {Patrick Riley and Manuela Veloso},
title = {On Behavior Classification in Adversarial
Environments},
booktitle = {Distributed Autonomous Robotic Systems 4},
pages = {371--380},
publisher = {Springer-Verlag},
year = 2000,
editor = {Lynne E. Parker and George Bekey and Jacob Barhen},
abstract = {In order for robotic systems to be successful in
domains with other agents possibly interfering with
the accomplishing of goals, the agents must be able
to adapt to the opponents' behavior. The more
quickly the agents can respond to a new situation,
the better they will perform. We present an approach
to doing adaptation which relies on classification
of the current adversary into predefined adversary
classes. For feature extraction, we present a
windowing technique to abstract useful but not
overly complicated features. In order to take into
account the spatial locality of topological
differences, we use a previously developed
similarity metric. The feature extraction and
classification steps are fully implemented in the
domain of simulated robotic soccer, and experimental
results are presented. },
bib2html_pubtype = {Refereed Conference},
bib2html_rescat = {Opponent and Teammate Modeling},
bib2html_funding = {CoABS,ActiveTemplates},
}
Generated by bib2html.pl (written by Patrick Riley ) on Tue Oct 09, 2007 00:00:13
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