Adapting virtual agent interaction style with reinforcement learning to enhance affective engagement

These findings highlight the potential of adaptive agents to personalize interaction strategies in emotionally relevant contexts, even when the subjective user experience appears similar to that of static systems. The ability to align communicative behavior with user personality profiles supports the feasibility of deploying such models in long-term interventions, where maintaining user motivation and engagement is essential.