Paper Contents
Abstract
As mental health concerns continue to rise, the need for accessible and consistent psychological support has driven significant progress in AI-enabled therapeutic technologies. One such advancement is the development of personalized chatbot therapists, which provide users with discreet, always-available emotional support. This study examines the design and implications of a chatbot capable of real-time emotional adaptation using reinforcement learningtechniques. By interpreting user feedbackwhether affirming or criticalthe system learns to adjust its conversational responses to better resonate with the individuals emotional state and improve its therapeutic impact. Prior research demonstrates that AI can identify affective cues through various channels, including language patterns, tone, and interaction frequency (Zhou et al., 2019; Tielman et al., 2019). When these systems respond with appropriate emotional alignment, they can foster a sense of empathy and trust, akin to human counselors (Quill, 2021; Tot
Copyright
Copyright © 2025 Aadhya Sharma. This is an open access article distributed under the Creative Commons Attribution License.
