Enhancing HVAC Control Systems through Transfer Learning with Deep Reinforcement Learning Agents

Link to Research - https://www.sciencedirect.com/science/article/pii/S2666955224000017

Installation

In a conda environment, run the following code.

git clone https://github.com/kad99kev/EHCSTLDRL.git
pip install -e .

Running an experiment.

Before running an experiment, the Docker environment needs to be built first. This can be done by running:

ehcs build

Once the Docker container is built, there are different options available:

1. controller - Will run an experiment using a rule-based controller agent.
2. train - Will train a Deep RL agent.
3. test- Will test a trained Deep RL agent.

The commands can be run as follows:

ehcs command_name -c path/to/config

Sample configuration files for PPO and SAC are given in configs/

Experiment tracking with Weights and Biases is supported. Enter the information required in a wandb section of the configuration file to enable experiment tracking.