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Michael Beetz, Freek Stulp, Alexandra Kirsch, Armin Müller, and Sebastian Buck. Autonomous Robot Controllers Capable
of Acquiring Repertoires of Complex Skills. In RoboCup-2003: The Seventh RoboCup Competitions and Conferences, Springer
Verlag, 2003.
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[PDF]65.8kB
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Due to the complexity and sophistication of the skills needed in real world tasks, the development of autonomous robot controllers
requires an ever increasing application of learning techniques. To date, however, learning steps are mainly executed in isolation
and only the learned code pieces become part of the controller. This approach has several drawbacks: the learning steps themselves
are undocumented and not executable. In this paper, we extend an existing control language with constructs for specifying
control tasks, process models, learning problems, exploration strategies, etc. Using these constructs, the learning problems
can be represented explicitly and transparently and, as they are part of the overall program implementation, become executable.
With the extended language we rationally reconstruct large parts of the action selection module of the Agilo2001 autonomous
soccer robots.
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@InProceedings{beetz03autonomous,
title = {Autonomous Robot Controllers Capable of Acquiring Repertoires of Complex Skills},
author = {Michael Beetz and Freek Stulp and Alexandra Kirsch and Armin M\"uller and Sebastian Buck},
booktitle = {{R}obo{C}up-2003: The Seventh {R}obo{C}up Competitions and Conferences},
year = {2003},
editor = {Daniel Polani and Andrea Bonarini and Brett Browning and Kazuo Yoshida},
publisher = {Springer Verlag},
abstract = {Due to the complexity and sophistication of the skills needed in real world tasks, the development of autonomous robot controllers requires an ever increasing application of learning techniques. To date, however, learning steps are mainly executed in isolation and only the learned code pieces become part of the controller. This approach has several drawbacks: the learning steps themselves are undocumented and not executable. In this paper, we extend an existing control language with constructs for specifying control tasks, process models, learning problems, exploration strategies, etc. Using these constructs, the learning problems can be represented explicitly and transparently and, as they are part of the overall program implementation, become executable. With the extended language we rationally reconstruct large parts of the action selection module of the Agilo2001 autonomous soccer robots.},
bib2html_pubtype = {Refereed Conference Paper},
bib2html_rescat = {RoboCup},
file = {ROBOCUP-SYMP-03-Beetz-etal.pdf:http\://www9.in.tum.de/publications/2003/ROBOCUP-SYMP-03-Beetz-etal.pdf:PDF}
}
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