When are Kalman-Filter Restless Bandits Indexable?
Dance, Christopher R., Silander, Tomi
–Neural Information Processing Systems
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}.
Neural Information Processing Systems
Dec-31-2015