AI RESEARCH
Optimal Data Acquisition for Reinforcement Learning: A Large Deviations Perspective
arXiv CS.LG
•
ArXi:2605.28675v1 Announce Type: new Data acquisition efficiency is a central challenge in deploying reinforcement learning in business and healthcare operations, where interactions are costly, slow, and often involve humans in the loop. This paper develops a unified large deviations framework for data acquisition in infinite-horizon reinforcement learning. We