4 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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…
Hierarchical Decentralized Stochastic Control for Cyber-Physical Systems
Kesav Kaza, Ramachandran Anantharaman, Rahul Meshram
This paper introduces a two-timescale hierarchical decentralized control architecture for Cyber-Physical Systems (CPS). The system consists of a global controller (GC), and N local…
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…
Simulation Based Algorithms for Markov Decision Processes and Multi-Action Restless Bandits
Rahul Meshram, Kesav Kaza
We consider multi-dimensional Markov decision processes and formulate a long term discounted reward optimization problem. Two simulation based algorithms---Monte Carlo rollout poli…