Hopes#
What’s in the box?#
HOPES, which stands for HVAC optimisation with Off Policy Evaluation and Selection, is a Python package for evaluating and selecting RL-based control policies. It offers a set of estimators and tools to evaluate the performance of a target policy, compared to a baseline policy (characterized by an offline logged dataset), using off-policy evaluation techniques. It’s particularly suited for the context of HVAC control, where the target policy is an RL-based controller and the baseline policies are rule-based controllers.
Why Hopes?#
Hopes is designed to be a flexible and easy-to-use package for evaluating and selecting RL-based control policies. Imagine you have a dataset of logged actions and observations from a building HVAC system, and you want to evaluate the performance of one or several RL-based controller. Hopes provides a set of tools to help you do that, including:
Estimators for evaluating the performance of a target policy compared to a baseline policy.
Tools for selecting the best policy among a set of candidate policies.
Tools for visualizing the results of the evaluation and selection process.
Dataset preprocessing tools to prepare the data for evaluation.
Installation#
Supported Python versions: 3.10+
From PyPI
1pip install hopes
From source (development version)
1git clone https://github.com/airboxlab/hopes.git
2cd hopes
3# using poetry
4poetry install
5# using pip
6pip install -r requirements.txt