RLEM brings together researchers and industry practitioners for the advancement of (deep) reinforcement learning (RL) in the built environment as it is applied for managing energy in civil infrastructure systems (energy, water, transportation).
This repository holds the source files that are used to build and maintain the rlem-workshop.net website. The website theme is taken from jekyll-theme-conference.
Follow these instructions to install Ruby and Jekyll on MacOS.
Bundle the website dependencies:
bundleFinally, build and run the site locally:
bundle exec jekyll serve --trace --watchA _site directory will be created that holds the website content and ideally, the content should not be manually edited nor pushed to the remote branch of this repository.
The website is located at rlem-workshop.net and uses GitHub Actions for continuous deployment.
To make changes to the website, commit changes to the main branch and push to the remote branch. The build.yml workflow will run the jekyll build remotely and deploy the site content to the gh-pages branch. Another Github Action workflow, handled by GitHub will re-build the website using the content in gh-pages.
Do not directly edit gh-pages branch!