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Conditions for indexability of restless bandits and an $\mathcal{O}\!\left(K^3\right)$ algorithm to compute Whittle index

Part of: Mathematical economics Numerical methods in calculus of variations and optimal control

Published online by Cambridge University Press:  14 June 2022

Nima Akbarzadeh Open the ORCID record for Nima Akbarzadeh [Opens in a new window]  and
Aditya Mahajan
Nima Akbarzadeh*
Affiliation:
McGill University
Aditya Mahajan*
Affiliation:
McGill University
*
*Postal address: Department of Electrical and Computer Engineering, McGill University, 3480 Rue University, Montréal, QC H3A 0E9.
*Postal address: Department of Electrical and Computer Engineering, McGill University, 3480 Rue University, Montréal, QC H3A 0E9.
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Abstract

Restless bandits are a class of sequential resource allocation problems concerned with allocating one or more resources among several alternative processes where the evolution of the processes depends on the resources allocated to them. Such models capture the fundamental trade-offs between exploration and exploitation. In 1988, Whittle developed an index heuristic for restless bandit problems which has emerged as a popular solution approach because of its simplicity and strong empirical performance. The Whittle index heuristic is applicable if the model satisfies a technical condition known as indexability. In this paper, we present two general sufficient conditions for indexability and identify simpler-to-verify refinements of these conditions. We then revisit a previously proposed algorithm called the adaptive greedy algorithm which is known to compute the Whittle index for a sub-class of restless bandits. We show that a generalization of the adaptive greedy algorithm computes the Whittle index for all indexable restless bandits. We present an efficient implementation of this algorithm which can compute the Whittle index of a restless bandit with K states in $\mathcal{O}\!\left(K^3\right)$ computations. Finally, we present a detailed numerical study which affirms the strong performance of the Whittle index heuristic.

Keywords

Multi-armed banditsrestless banditsWhittle indexindexabilitystochastic schedulingresource allocation

MSC classification

Primary: 90C40: Markov and semi-Markov decision processes
Secondary: 90C39: Dynamic programming 49M20: Methods of relaxation type 91B32: Resource and cost allocation

Information

Type
Original Article
Information
Advances in Applied Probability , Volume 54 , Issue 4 , December 2022 , pp. 1164 - 1192
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Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust

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