We show that the fluid approximation to Whittle's index policy for restless bandits has a globally asymptotically stable equilibrium point when the bandits move on just three states. It follows that in this case the index policy is asymptotic optimal. In [2] we investigated properties of an index policy for restless bandits that had been the subject of an interesting paper by Whittle [3]. We showed that if the fluid approximation to his index policy has a globally asymptotically stable equilibrium point then it is asymptotically optimal, for the problem of choosing which m out of n bandits to make active, as m, n-- 0, with m/n = a. We observed that the existence of such a point is guaranteed when the bandits move on just k = 2 states. ...
We consider optimal sequential allocation in the context of the so-called stochastic multi-armed ban...
We provide a framework to analyse control policies for the restless Markovian bandit model, under bo...
We consider a general multi-armed bandit problem with correlated (and simple contextual and restless...
We study the asymptotic optimal control of multi-class restless bandits. A restless bandit is a cont...
The class of restless bandits as proposed by Whittle (1988) have long been known to be intractable. ...
We study the asymptotic optimal control of multi-class restless bandits. A restless bandit is a cont...
We evaluate the performance of Whittle index policy for restless Markovian bandits, when the number ...
We investigate the optimal allocation of effort to a collection of n projects. The projects are &apo...
International audienceThe multi-armed restless bandit framework allows to model a wide variety of de...
Includes bibliographical references (p. 5).Supported by the ARO. DAAL03-92-G-0115 Supported by Sieme...
International audienceWe develop a unifying framework to obtain efficient index policies for restles...
We propose an asymptotically optimal heuristic, which we termed the Randomized Assignment Control (R...
Abstract. In the classical bandit problem, the arms of a slot machine are always available. This pap...
We study a finite-horizon restless multi-armed bandit problem with multiple actions, dubbed as R(MA)...
We consider a restless multiarmed bandit in which each arm can be in one of two states. When an arm ...
We consider optimal sequential allocation in the context of the so-called stochastic multi-armed ban...
We provide a framework to analyse control policies for the restless Markovian bandit model, under bo...
We consider a general multi-armed bandit problem with correlated (and simple contextual and restless...
We study the asymptotic optimal control of multi-class restless bandits. A restless bandit is a cont...
The class of restless bandits as proposed by Whittle (1988) have long been known to be intractable. ...
We study the asymptotic optimal control of multi-class restless bandits. A restless bandit is a cont...
We evaluate the performance of Whittle index policy for restless Markovian bandits, when the number ...
We investigate the optimal allocation of effort to a collection of n projects. The projects are &apo...
International audienceThe multi-armed restless bandit framework allows to model a wide variety of de...
Includes bibliographical references (p. 5).Supported by the ARO. DAAL03-92-G-0115 Supported by Sieme...
International audienceWe develop a unifying framework to obtain efficient index policies for restles...
We propose an asymptotically optimal heuristic, which we termed the Randomized Assignment Control (R...
Abstract. In the classical bandit problem, the arms of a slot machine are always available. This pap...
We study a finite-horizon restless multi-armed bandit problem with multiple actions, dubbed as R(MA)...
We consider a restless multiarmed bandit in which each arm can be in one of two states. When an arm ...
We consider optimal sequential allocation in the context of the so-called stochastic multi-armed ban...
We provide a framework to analyse control policies for the restless Markovian bandit model, under bo...
We consider a general multi-armed bandit problem with correlated (and simple contextual and restless...