Providing behavioral health interventions via smartphones allows these interventions to be adapted to the changing behavior, preferences, and needs of individuals. This can be achieved through reinforcement learning (RL), a sub-area of machine learning. However, many challenges could affect the effectiveness of these algorithms in the real world. We provide guidelines for decision-making.

中文翻译：

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用于优化行为健康移动应用程序的自适应学习算法：设计决策指南

通过智能手机提供行为健康干预可以使这些干预适应个人不断变化的行为、偏好和需求。这可以通过机器学习的一个子领域强化学习 (RL) 来实现。然而，许多挑战可能会影响这些算法在现实世界中的有效性。我们提供决策指导。