Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions

arXiv:2203.02605v3 Announce Type: replace-cross
Abstract: In recent years, reinforcement learning (RL) has acquired a prominent position in health-related sequential decision-making problems, gaining traction as a valuable tool for delivering adaptive interventions (AIs). However, in part due to a poor synergy between the methodological and the applied communities, its real-life application is still limited and its potential is still to be realized. To address this gap, our work provides the first unified technical survey on RL methods, complemented with case studies, …

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