May 24, 2012 · This problem can be cast into a restless multi-armed bandit (RMAB) problem that is intractable for its exponential computation complexity. A ...
1) When studying the optimality of the myopic policy, most existing works focus on the homogeneous case where each channel follows the identical Markov chain ...
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May 31, 2012 · On Optimality of Myopic Policy for Restless. Multi-armed Bandit Problem with Non i.i.d.. Arms and Imperfect Detection. Kehao Wang. Lin Chen.
The second thrust is to establish sufficient conditions to guarantee the optimality of the myopic policy in some specific instances of restless bandit scenarios ...
Oct 17, 2013 · This problem can be cast into a restless multiarmed bandit (RMAB) problem, which is intractable for its exponential computation complexity.
Bibliographic details on On Optimality of Myopic Policy for Restless Multi-armed Bandit Problem with Non i.i.d. Arms and Imperfect Detection.
The objective is to design a scheduling policy that maximizes the expected accumulated discounted reward over a finite or infinite horizon. The considered ...
A recent follow-up work [6] has extended the optimality of the myopic policy to all N under the condition of p11 ≥ p01. For independent and non-identical ...
In this paper, we perform an analytical study on the optimality of the myopic policy under imperfect sensing for the considered RMAB problem. Specifically, for ...
The decision problem can be cast into a restless multiarmed bandit. (RMAB) problem, which is proved to be pSPACE-hard [1], and very few results are reported on ...