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Gregory Kuhlmann and Peter Stone.
Progress in Learning 3 vs. 2 Keepaway. In Daniel Polani, Brett Browning, Andrea Bonarini, and Kazuo Yoshida, editors,
RoboCup-2003: Robot Soccer World Cup VII, Springer Verlag, Berlin, 2004.
Some simulations
of keepaway referenced in the paper.
[PDF]340.8kB [postscript]544.0kB
(unavailable)
@InCollection(LNAI2003-keepaway,
author="Gregory Kuhlmann and Peter Stone",
title="Progress in Learning 3 vs.~2 Keepaway",
booktitle= "{R}obo{C}up-2003: Robot Soccer World Cup {VII}",
Editor="Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida",
Publisher="Springer Verlag",address="Berlin",year="2004",
abtract={
Reinforcement learning has been successfully applied
to several subtasks in the RoboCup simulated soccer
domain. Keepaway is one such task. One notable
success in the keepaway domain has been the
application of SMDP Sarsa(lambda) with tile-coding
function approximation. However, this success was
achieved with the help of some significant task
simplifications, including the delivery of complete,
noise-free world-state information to the agents.
Here we demonstrate that this task simplification was
unnecessary and further extend the previous empirical
results on this task.
},
wwwnote={Some <a href="http://www.cs.utexas.edu/users/AustinVilla/sim/keepaway/">simulations of keepaway</a> referenced in the paper.},
)
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