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20172026
most citedSimulation Based Algorithms for Markov Decision Processes and Multi-Action Restless Bandits

4 citations · 4 across the 10 of their papers we have counts for

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eess.SY2026

Optimal Threshold Type Policies for Partially Observable Restless Bandits

Anu Krishna, Rahul Meshram, Kesav Ram Kaza

We study a finite-state partially observable restless multi-armed bandit (PO-RMAB) motivated by resource-constrained wildlife monitoring. The underlying condition of each location…

eess.SY2026

Outcome-Fair Restless Multi-Armed Bandits for Stochastic Deadline Scheduling

Shakti Sharma, Rahul Meshram

We study a restless multi-armed bandit (RMAB) problem for a stochastic deadline scheduling application. RMAB problems are solved using the Whittle index policy. The goal in RMAB is…