Pascal Poupart
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: ppoupart@cs.toronto.edu
Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly@cs.toronto.edu
Abstract
We propose a new approach to value-directed belief state approximation
for POMDPs. The value-directed model allows one to choose approximation
methods for belief state monitoring that have a small impact on
decision quality. Using a vector space analysis of the problem,
we devise two new search procedures for selecting an approximation
scheme that have much better computational properties than existing
methods. Though these provide looser error bounds, we show
empirically that they have a similar impact on decision quality
in practice, and run up to two orders of magnitude more quickly.
To appear, UAI-01
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