SOURCE-LINKED INTELLIGENCE
Affective Agent: On-Device Personalized Intervention Reasoning for Wearable Systems
Affective computing has advanced wearable state inference, but on-device reasoning about whether, when, and how to intervene remains challenging. We present Affective Agent, a three-layer reference architecture for personalized intervention reasoning under uncertainty on wearable-class hardware. It combines a compact sub-billion-parameter language model with physiological evidence, context, and user history to decide whether, when, and how to intervene, without cloud dependency or per-user retraining. The architecture is organized into three interacting layers (perception, personalization, and
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T01:01:44.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.