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Graphical Models for Bandit Problems
release_l5vdorprcvdo3c3sagx4yftsaq
by
Kareem Amin, Michael Kearns, Umar Syed
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as a report
.
2012
Abstract
We introduce a rich class of graphical models for multi-armed bandit problems
that permit both the state or context space and the action space to be very
large, yet succinctly specify the payoffs for any context-action pair. Our main
result is an algorithm for such models whose regret is bounded by the number of
parameters and whose running time depends only on the treewidth of the graph
substructure induced by the action space.
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