mlsanityData to 7 Oct 2026

Field Study in Deploying Restless Multi-Armed Bandits: Assisting Non-Profits in Improving Maternal and Child Health

arXiv 2109.08075 ↗First posted 16 Sep 2021cs.LG cs.AIcited by 43

Not on the map. Why?

Abstract (arXiv)

The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work to assist non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing this limited resource, we developed a Restless Multi-Armed Bandits (RMABs) system. One key technical contribution in this system is a novel clustering method of offline historical data to infer unknown RMAB parameters. Our second major contribution is evaluation of our RMAB system in collaboration with an NGO, via a real-world service quality improvement study. The study compared strategies for optimizing service calls to 23003 participants over a period of 7 weeks to reduce engagement drops. We show that the RMAB group provides statistically significant improvement over other comparison groups, reducing ~ 30% engagement drops. To the best of our knowledge, this is the first study demonstrating the utility of RMABs in real world public health settings. We are transitioning our RMAB system to the NGO for real-world use.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 12 of its 44 references that are in the map. First posted on arXiv 16 Sep 2021.

Builds on

12 of 44 references.

References · 12

  1. 2014Online Clustering of Banditscited by 99
  2. 2019Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activitycited by 70
  3. 2020Collapsing Bandits and Their Application to Public Health Interventionscited by 47
  4. 2020Whittle index based Q-learning for restless bandits with average rewardcited by 43
  5. 2019Improved Algorithm on Online Clustering of Banditscited by 38
  6. 2019Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problemscited by 34
  7. 2021Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcarecited by 34
  8. 2017Non-Stationary Bandits with Habituation and Recovery Dynamicscited by 23
  9. 2019Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Datacited by 21
  10. 2021Q-Learning Lagrange Policies for Multi-Action Restless Banditscited by 20
  11. 2020Unifying Clustered and Non-stationary Banditscited by 11
  12. 2020Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessnesscited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 12; 2024: 9; 2025: 13; 2026: 3.

43 papers.

Sort:

By area:

  1. 2023A Survey of Contextual Optimization Methods for Decision Making under Uncertaintycited by 81
  2. 2025Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Informationcited by 25
  3. 2024A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Healthcited by 24
  4. 2024Application-Driven Innovation in Machine Learningcited by 24
  5. 2022Optimistic Whittle Index Policy: Online Learning for Restless Banditscited by 18
  6. 2022Socially Fair Reinforcement Learningcited by 13
  7. 2022Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Healthcited by 12
  8. 2023Optimal Algorithms for Latent Bandits with Cluster Structurecited by 11
  9. 2022Indexability is Not Enough for Whittle: Improved, Near-Optimal Algorithms for Restless Banditscited by 10
  10. 2023Policy Optimization for Personalized Interventions in Behavioral Healthcited by 9
  11. 2023Towards a Pretrained Model for Restless Bandits via Multi-arm Generalizationcited by 9
  12. 2024Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impactcited by 9
31 more
  1. 2022ADVISER: AI-Driven Vaccination Intervention Optimiser for Increasing Vaccine Uptake in Nigeriacited by 6
  2. 2022Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learningcited by 6
  3. 2023Equitable Restless Multi-Armed Bandits: A General Framework Inspired By Digital Healthcited by 6
  4. 2024Global Rewards in Restless Multi-Armed Banditscited by 6
  5. 2025Offline-to-online hyperparameter transfer for stochastic banditscited by 6
  6. 2024Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Banditscited by 5
  7. 2025Reinforcement learning with combinatorial actions for coupled restless banditscited by 5
  8. 2023Improved Policy Evaluation for Randomized Trials of Algorithmic Resource Allocationcited by 4
  9. 2023Limited Resource Allocation in a Non-Markovian World: The Case of Maternal and Child Healthcarecited by 4
  10. 2023Fairness for Workers Who Pull the Arms: An Index Based Policy for Allocation of Restless Bandit Taskscited by 3
  11. 2024Improving the Prediction of Individual Engagement in Recommendations Using Cognitive Modelscited by 3
  12. 2025Efficiently Solving Discounted MDPs with Predictions on Transition Matricescited by 2
  13. 2025Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Improved Message Delivery in Mobile Maternal Healthcited by 2
  14. 2025Beyond Listenership: AI-Predicted Interventions Drive Improvements in Maternal Health Behaviourscited by 2
  15. 2023Decision-Focused Evaluation: Analyzing Performance of Deployed Restless Multi-Arm Banditscited by 1
  16. 2024GINO-Q: Learning an Asymptotically Optimal Index Policy for Restless Multi-armed Banditscited by 1
  17. 2024The Digital Transformation in Health: How AI Can Improve the Performance of Health Systemscited by 1
  18. 2025VORTEX: Aligning Task Utility and Human Preferences through LLM-Guided Reward Shapingcited by 1
  19. 2023Adaptive Interventions for Global Health: A Case Study of Malariacited by 0
  20. 2023Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaborationcited by 0
  21. 2023Deploying ADVISER: Impact and Lessons from Using Artificial Intelligence for Child Vaccination Uptake in Nigeriacited by 0
  22. 2024A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible foodcited by 0
  23. 2025Optimal Control of Fluid Restless Multi-armed Bandits: A Machine Learning Approachcited by 0
  24. 2025From Restless to Contextual: A Thresholding Bandit Reformulation For Finite-horizon Improvementcited by 0
  25. 2025Non-Stationary Restless Multi-Armed Bandits with Provable Guaranteecited by 0
  26. 2025Lagrangian Relaxation for Multi-Action Partially Observable Restless Bandits: Heuristic Policies and Indexabilitycited by 0
  27. 2025AI Adoption in NGOs: A Systematic Literature Reviewcited by 0
  28. 2025Neural Index Policies for Restless Multi-Action Bandits with Heterogeneous Budgetscited by 0
  29. 2026SMaRT: Online Reusable Resource Assignment and an Application to Mediation in the Kenyan Judiciarycited by 0
  30. 2026Decisions and Deployment: The Five-Year SAHELI Project (2020-2025) on Restless Multi-Armed Bandits for Improving Maternal and Child Healthcited by 0
  31. 2026A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Interventioncited by 0