Reinforcement Learning to Increase the Reach of Brief Psychological Treatments in Resource Constrained Environments of the U.S. and Latin America
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Reinforcement learning (RL) is a process through which an intelligent agent learns via serial interactions what actions optimize a defined outcome (i.e., reward). In a number of studies, we are using RL to increase the efficiency and scalability of evidence-based brief psychotherapies such as cognitive behavioral therapy. In this session, we will review recent findings from this research, discuss new applications planned in the US and Honduras, and (as time permits) consider improvements in the RL algorithms reflecting important objectives of patients and health system partners.