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When are Kalman-filter restless bandits indexable?

Dance, Christopher R., Silander, Tomi

arXiv.org Machine LearningSep-15-2015

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 indexable in the sense that the 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 Schur-convexity and mechanical words, which are particular binary strings intimately related to palindromes.

data mining, machine learning, x-threshold word, (17 more...)

arXiv.org Machine Learning

1509.04541

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Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
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