From one building to many: transferability of a deep reinforcement learning agent for optimizing pollutant exposure and energy consumption
Abstract
Assessing transferability is essential for large-scale deployment of DRL-based indoor control system, enabling scalable improvements in energy efficiency, occupants' health, and sustainable building operation.
Fields of Study & Subjects
Building Energy and Comfort Optimization
Smart Grid Energy Management
Reinforcement Learning in Robotics
Publication details
- Journal / source
- Environmental Science Advances
- Publisher
- Royal Society of Chemistry (RSC)
- Volume
- 5
- Issue
- 5
- Pages
- 1292–1305
- Publication date
- 1 January 2026
- Language
- EN