Immediate action is required to combat climate change. The technology behind Cognizant NeuroAI brings automatic decision-making to the En-ROADS platform, a powerful climate change simulator. A decision-maker can be ready for any scenario: choosing an automatically generated policy that suits their needs best, with the ability to manually modify the policy and see its results. This tool is brought together under Project Resilience, a United Nations initiative to use AI for good.
En-ROADS is a climate change simulator developed by Climate Interactive. We have created a wrapper around the SDK to make it simple to use in a Python application which can be found in enroadspy. See enroads_runner.py for the main class that runs the SDK. The SDK is not included in this repository and access to it is very limited. If you would like to run this code, please contact Project Resilience at [email protected].
This project was created with Python 3.10.14. Run pip install -r requirements.txt to install the required packages. Then run python -m enroadspy.download_sdk to download the SDK. In order to download the SDK environment variables must be set.
We use 2 methods to evolve the policies: one is our own open-source version of NSGA-II implemented in PyTorch which is in evolution/. The other uses the pymoo library and is found in moo/.
See the notebooks in experiments/ for how to analyze the results of such evolution.
A demo app is available in app/ which displays the results of a pymoo evolution run. Run the app with python -m app.app
In order to deploy the app there is a provided Dockerfile. However, first access must be configured to load the SDK from the S3 bucket where it is stored. To build the Docker image use docker build -t enroads-demo . Then to run the container use docker run -p 8080:4057 --name enroads-demo-container enroads-demo