NeurIPS 2015poster17 citations
When are Kalman-Filter Restless Bandits Indexable?
Christopher R Dance, Tomi Silander
Abstract
We study the restless bandit associated with an extremely simple scalar Kalman filter model in discrete time. Under certain assumptions, we prove that the problem is {\it indexable} in the sense that the {\it Whittle index} is a non-decreasing function of the relevant belief state. In spite of the long history of this problem, this appears to be the first such proof. We use results about {\it Schur-convexity} and {\it mechanical words}, which are particularbinary strings intimately related to {\it palindromes}.
BibTeX
@inproceedings{NIPS2015_6d70cb65,
author = {Dance, Christopher R and Silander, Tomi},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {When are Kalman-Filter Restless Bandits Indexable?},
url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/6d70cb65d15211726dcce4c0e971e21c-Paper.pdf},
volume = {28},
year = {2015}
}