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 reasoning), adapting to individual users through host-managed structured memory evolution rather...
| Authors | Reina Mun, Zishen Wan, Vijay Janapa Reddi |
|---|---|
| Primary category | cs.AI |
| Published | 11 September 2026 |
| Last updated at source | 11 September 2026 |
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