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@inproceedings(ICML06-bikram,
author="Bikramjit Banerjee and Gregory Kuhlmann and Peter Stone",
title="Value Function Transfer for General Game Playing",
Booktitle="{ICML} workshop on Structural Knowledge Transfer for Machine Learning",
month="June",year="2006",
abstract={
We present value function transfer techniques for
General Game Playing (GGP) by Reinforcement
Learning. We focus on 2 player, alternate-move,
complete information board games and use the GGP
simulator and framework. Our approach is
two-pronged: first we extract knowledge about
crucial regions in the value-function space of any
game in the genre. Then for each target game, we
generate a smaller version of this game and extract
symmetry information from the board setup. The
combined knowledge of value function and symmetry
allows us to achieve significant transfer via
Reinforcement Learning, to larger board games using
only a limited size of state-space by virtue of
exploiting symmetry.
},
wwwnote={ICML 2006 workshop on Structural Knowledge Transfer for Machine Learning},
)