5 papers
Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions
Asim H. Gazi, Yongyi Guo, Daiqi Gao +3
Reinforcement learning (RL) has achieved remarkable success in real-world decision-making across diverse domains, including gaming, robotics, online advertising, public health, and…
Reproducible workflow for online AI in digital health
Susobhan Ghosh, Bhanu T. Gullapalli, Daiqi Gao +5
Online artificial intelligence (AI) algorithms are an important component of digital health interventions. These online algorithms are designed to continually learn and improve the…
Active Measuring in Reinforcement Learning With Delayed Negative Effects
Daiqi Gao, Ziping Xu, Aseel Rawashdeh +2
Measuring states in reinforcement learning (RL) can be costly in real-world settings and may negatively influence future outcomes. We introduce the Actively Observable Markov Decis…
SigmaScheduling: Uncertainty-Informed Scheduling of Decision Points for Intelligent Mobile Health Interventions
Asim H. Gazi, Bhanu Teja Gullapalli, Daiqi Gao +3
Timely decision making is critical to the effectiveness of mobile health (mHealth) interventions. At predefined timepoints called "decision points," intelligent mHealth systems suc…
Harnessing Causality in Reinforcement Learning With Bagged Decision Times
Daiqi Gao, Hsin-Yu Lai, Predrag Klasnja +1
We consider reinforcement learning (RL) for a class of problems with bagged decision times. A bag contains a finite sequence of consecutive decision times. The transition dynamics…