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reBandit: Random Effects based Online RL algorithm for Reducing Cannabis Use
Feb. 28, 2024, 5:43 a.m. | Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen Walton, Susan Murphy
cs.LG updates on arXiv.org arxiv.org
Abstract: The escalating prevalence of cannabis use, and associated cannabis-use disorder (CUD), poses a significant public health challenge globally. With a notably wide treatment gap, especially among emerging adults (EAs; ages 18-25), addressing cannabis use and CUD remains a pivotal objective within the 2030 United Nations Agenda for Sustainable Development Goals (SDG). In this work, we develop an online reinforcement learning (RL) algorithm called reBandit which will be utilized in a mobile health study to deliver …
abstract algorithm arxiv cannabis challenge cs.ai cs.lg effects gap health pivotal public public health random treatment type united
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