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Trey Smith, David R. Thompson, and David S. Wettergreen. In Proc. Int. Conf. on Applied Planning and Scheduling (ICAPS), 2007.
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The state of a POMDP can often be factored into a tuple of n state variables. The corresponding flat model, with size exponential in n, may be intractably large. We present a novel method called conditionally irrelevant variable abstraction (CIVA) for losslessly compressing the factored model, which is then expanded into an exponentially smaller flat model in a representation compatible with many existing POMDP solvers. We applied CIVA to previously intractable problems from a robotic exploration domain. We were able to abstract, expand, and approximately solve POMDPs that had up to 1024 states in the uncompressed flat representation.
@InProceedings{smith07:civa,
author = {Trey Smith and David R. Thompson and David S. Wettergreen},
title = {Generating Exponentially Smaller {POMDP} Models Using Conditionally Irrelevant Variable Abstraction},
booktitle = {Proc. Int. Conf. on Applied Planning and Scheduling (ICAPS)},
year = 2007,
}
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