# tsinghua-fib-lab/DRL-urban-planning

<https://repo.masters-masters.com/en/repos/tsinghua-fib-lab/DRL-urban-planning>

[Home](https://repo.masters-masters.com/en) › [tsinghua-fib-lab](https://repo.masters-masters.com/en/owners/tsinghua-fib-lab) › [DRL-urban-planning](https://repo.masters-masters.com/en/repos/tsinghua-fib-lab/DRL-urban-planning)

tsinghua-fib-lab/DRL-urban-planning has 312 stars on GitHub. Its RepoMasters card: Alpha tier. A deep reinforcement learning (DRL) based approach for spatial…

| Field | Value |
| --- | --- |
| Owner | [tsinghua-fib-lab](https://repo.masters-masters.com/en/owners/tsinghua-fib-lab) |
| Stars | 312 |
| Forks | 52 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2023 |
| Topics | graph-neural-networks, reinforcement-learning, spatial-planning, urban-planning |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [tsinghua-fib-lab/DRL-urban-planning](https://github.com/tsinghua-fib-lab/DRL-urban-planning) |

## Repository

A deep reinforcement learning (DRL) based approach for spatial layout of land use and roads in urban communities. (Nature Computational Science)

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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