A three-agent reinforcement learning framework with domain-informed surrogate rewards outperforms single-agent and random policies for personalizing dyadic medication-adherence interventions in simulation.
IEEE Transactions on Computational Social Systems9(5), 1505–1514 (2021)
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Reinforcement Learning on Dyads to Enhance Medication Adherence
A three-agent reinforcement learning framework with domain-informed surrogate rewards outperforms single-agent and random policies for personalizing dyadic medication-adherence interventions in simulation.