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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A PyTorch library for all things Reinforcement Learning (RL) for Combinatorial Optimization (CO)
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| 2026-08-05 | 896 |
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Today
+1 stars today
This week
+2 stars this week
This month
+12 stars this month
Momentum
6.0
growth rate 0.22%/day
</br> <div align="center"> <img src="https://raw.githubusercontent.com/ai4co/assets/main/svg/rl4co_animated_full.svg" alt="AI4CO Logo" style="width: 40%; height: auto;"> </br></br> <a href="https://pytorch.org/get-started/locally/"><img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-ee4c2c?logo=pytorch&logoColor=white"></a> <a href="https://pytorchlightning.ai/"><img alt="Lightning" src="https://img.shields.io/badge/-Lightning-792ee5?logo=pytorchlightning&logoColor=white"></a> <a href="https://github.com/pytorch/rl"><img alt="base: TorchRL" src="https://img.shields.io/badge/base-TorchRL-red"></a> <a href="https://hydra.cc/"><img alt="config: Hydra" src="https://img.shields.io/badge/config-Hydra-89b8cd"></a> <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> <a href="https://join.slack.com/t/ai4co-community/shared_invite/zt-3jsdjs3ec-3KHdV3HwanL884mq_9tyYw"><img alt="Slack" src="https://img.shields.io/badge/slack-chat-611f69.svg?logo=slack"></a> <a href="https://opensource.org/licenses/MIT"><img alt="License: MIT" src="https://img.shields.io/badge/License-MIT-red.svg"></a> <a href="https://colab.research.google.com/github/ai4co/rl4co/blob/main/examples/1-quickstart.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://pypi.org/project/rl4co"><img alt="PyPI" src="https://img.shields.io/pypi/v/rl4co?logo=pypi"></a> <a href="https://app.codecov.io/github/ai4co/rl4co/tree/main/rl4co"><img alt="Codecov" src="https://codecov.io/github/ai4co/rl4co/tree/main/badge.svg"></a> <a href="https://github.com/ai4co/rl4co/actions/workflows/tests.yml"><img alt="Test" src="https://github.com/ai4co/rl4co/actions/workflows/tests.yml/badge.svg"></a> <p> <a href="https://rl4co.ai4co.org/"><strong>Documentation</strong></a> | <a href="#getting-started"><strong>Getting Started</strong></a> | <a href="#usage"><strong>Usage</strong></a> | <a href="#contributing"><strong>Contributing</strong></a> | <a href="https://arxiv.org/abs/2306.17100"><strong>Paper</strong></a> | <a href="#join-us"><strong>Join Us</strong></a> </p> </div> An extensive Reinforcement Learning (RL) for Combinatorial Optimization (CO) benchmark. Our goal is to provide a unified framework for RL-based CO algorithms, and to facilitate reproducible research in this field, decoupling the science from the engineering. RL4CO is built upon: - [TorchRL](https://github.com/pytorch/rl): official PyTorch framework for RL algorithms and vectorized environments on GPUs - [TensorDict](https://github.com/pytorch-labs/tensordict): a library to easily handle heterogeneous data such as states, actions and rewards - [PyTorch Lightning](https://github.com/Lightning-AI/lightning): a lightweight PyTorch wrapper for high-performance AI research - [Hydra](https://github.com/facebookresearch/hydra): a framework for elegantly configuring complex applications <div align="center"> <img src="https://github.com/ai4co/rl4co/assets/48984123/0e409784-05a9-4799-b7aa-6c0f76ecf27f" alt="RL4CO-Overview" style="max-width: 90%;"> </div> We offer flexible and efficient implementations of the following policies: - **Constructive**: learn to construct a solution from scratch - _Autoregressive (AR)_: construct solutions one step at a time via a decoder - _NonAutoregressive (NAR)_: learn to predict a heuristic, such as a heatmap, to then construct a solution - **Improvement**: learn to improve a pre-existing solution <div align="center"> <img src="https://github.com/ai4co/rl4co/assets/48984123/9e1f32f9-9884-49b9-b6cd-364861cc8fe7" alt="RL4CO-Policy-Overview" style="max-width: 90%;"> </div> We provide several utilities and modularization. For example, we modularize reusable components such as _environment embeddings_ that can easily be swapped to [solve new problems](https://github.com/ai4co/rl4co/blob/main/examples/3-creating-new-env-mod
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Read on GitHub
Federico Berto · @RadicalNumerics, @AI4CO · Japan
1.0k
172
160
Junyoung Park · United States
51
41
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35
24
13
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Michael Poli · Radical Numerics
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Haoran Ye · Peking University · China
2
Sangyun_LEE · CJ OliveNetworks · South Korea
2
Emmanuel Ferdman · Israel
1
Ikko Eltociear Ashimine · Japan
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:00964b388cf826e7, topic:reinforcement-learning, desc:reinforcement learning, readme:reinforcement learning
matched fp:00964b388cf826e7, topic:benchmark