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11 changes: 5 additions & 6 deletions README.md
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@@ -1,18 +1,17 @@
# RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation Research

:one: First work to incorporate end-to-end vehicle routing model in a modern RL platform (CleanRL)
1️⃣ First work to incorporate end-to-end vehicle routing model in a modern RL platform (CleanRL)

:zap: Speed up the training of Attention Model by 8 times (25hours $\to$ 3 hours)
Speed up the training of Attention Model by 8 times (25hours --> 3 hours)

:mag_right: A flexible framework for developing *model*, *algorithm*, *environment*, and *search* for operation research
🔎 A flexible framework for developing *model*, *algorithm*, *environment*, and *search* for operation research

## News

- 13/04/2023: We release web demo on [Hugging Face 🤗](https://huggingface.co/spaces/cpwan/RLOR-TSP)!
- 24/03/2023: We release our paper on [arxiv](https://arxiv.org/abs/2303.13117)!
- 20/03/2023: We release demo and pretrained checkpoints!
- 20/03/2023: We release jupyter lab demo and pretrained checkpoints!
- 10/03/2023: We release our codebase!


## Demo
We provide inference demo on colab notebook:

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4 changes: 4 additions & 0 deletions _config.yml
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remote_theme: pages-themes/cayman@v0.2.0
plugins:
- jekyll-remote-theme
google_analytics: G-JJM1CJ0V7J
9 changes: 9 additions & 0 deletions _includes/head-custom-google-analytics.html
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@@ -0,0 +1,9 @@
<!-- Google tag (gtag.js) -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-JJM1CJ0V7J"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());

gtag('config', 'G-JJM1CJ0V7J');
</script>