110 citations · 141 across the 5 of their papers we have counts for
4 papers · 1 filter
Networked Restless Multi-Armed Bandits for Mobile Interventions
Han-Ching Ou, Christoph Siebenbrunner, Jackson Killian +4
Motivated by a broad class of mobile intervention problems, we propose and study restless multi-armed bandits (RMABs) with network effects. In our model, arms are partially recharg…
Q-Learning Lagrange Policies for Multi-Action Restless Bandits
Jackson A. Killian, Arpita Biswas, Sanket Shah +1
Multi-action restless multi-armed bandits (RMABs) are a powerful framework for constrained resource allocation in which independent processes are managed. However, previous wor…
Collapsing Bandits and Their Application to Public Health Interventions
Aditya Mate, Jackson A. Killian, Haifeng Xu +2
We propose and study Collpasing Bandits, a new restless multi-armed bandit (RMAB) setting in which each arm follows a binary-state Markovian process with a special structure: when…
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
Jackson A. Killian, Bryan Wilder, Amit Sharma +4
Digital Adherence Technologies (DATs) are an increasingly popular method for verifying patient adherence to many medications. We analyze data from one city served by 99DOTS, a phon…