Double deep Q-network

This study aims to develop and evaluate an advanced control method for acceptable indoor air quality (e.g., particulate matter and CO2) with low energy consumption in a residential space. A ventilation system, an air purifier, and a kitchen hood system are installed in the testbed to maintain a healthy IAQ. To accomplish the objective, we use a double deep Q-network (DDQN) which is one of the reinforcement learning. This study utilizes a co-simulation platform with EnergyPlus and Python.