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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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Showing 2021Show all

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cs.LG2021

Indexability and Rollout Policy for Multi-State Partially Observable Restless Bandits

Rahul Meshram, Kesav Kaza

Restless multi-armed bandits with partially observable states has applications in communication systems, age of information and recommendation systems. In this paper, we study mult…

eess.SY2021

Monte Carlo Rollout Policy for Recommendation Systems with Dynamic User Behavior

Rahul Meshram, Kesav Kaza

We model online recommendation systems using the hidden Markov multi-state restless multi-armed bandit problem. To solve this we present Monte Carlo rollout policy. We illustrate n…