455 citations · 880 across the 33 of their papers we have counts for
34 papers
Modeling Mobile Health Users as Reinforcement Learning Agents
Eura Shin, Siddharth Swaroop, Weiwei Pan +2
Mobile health (mHealth) technologies empower patients to adopt/maintain healthy behaviors in their daily lives, by providing interventions (e.g. push notifications) tailored to the…
Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani +3
Dental disease is one of the most common chronic diseases despite being largely preventable. However, professional advice on optimal oral hygiene practices is often forgotten or ab…
Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines
Anna L. Trella, Kelly W. Zhang, Inbal Nahum-Shani +3
Online reinforcement learning (RL) algorithms are increasingly used to personalize digital interventions in the fields of mobile health and online education. Common challenges in d…
Estimating causal effects with optimization-based methods: A review and empirical comparison
Martin Cousineau, Vedat Verter, Susan A. Murphy +1
In the absence of randomized controlled and natural experiments, it is necessary to balance the distributions of (observable) covariates of the treated and control groups in order…
Counterfactual inference in sequential experiments
Raaz Dwivedi, Katherine Tian, Sabina Tomkins +3
We consider after-study statistical inference for sequentially designed experiments wherein multiple units are assigned treatments for multiple time points using treatment policies…
Comparison and Unification of Three Regularization Methods in Batch Reinforcement Learning
Sarah Rathnam, Susan A. Murphy, Finale Doshi-Velez
In batch reinforcement learning, there can be poorly explored state-action pairs resulting in poorly learned, inaccurate models and poorly performing associated policies. Various r…