A Hybrid Classifier-Guided Deep Q-Learning Approach for Multi-Objective Building Environment Management
A comfort-aware reinforcement learning (RL) framework is presented for intelligent indoor environment control in smart buildings. The system comprises three primary components: a data-driven comfort classifier, a lightweight indoor environment simulator, and a Deep Q-Network (DQN) control agent. A synthetic dataset, re...