tsinghua-fib-lab / DRL-urban-planning

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

Date Created 2023-01-02 (about a year ago)

Commits 31 (last one 25 days ago)

Stargazers 210 (3 this week)

Watchers 3 (0 this week)

Forks 41

License mit

Ranking

RepositoryStats indexes 589,134 repositories, of these tsinghua-fib-lab/DRL-urban-planning is ranked #174,159 (70th percentile) for total stargazers, and #424,515 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #3,958/17,281.

tsinghua-fib-lab/DRL-urban-planning is also tagged with popular topics, for these it's ranked: reinforcement-learning (#499/1319), graph-neural-networks (#151/584)

Other Information

tsinghua-fib-lab/DRL-urban-planning has Github issues enabled, there are 3 open issues and 17 closed issues.

There have been 1 release, the latest one was published on 2023-07-23 (about a year ago) with the name Release v0.1.

Homepage URL: https://rdcu.be/dlRPZ

All Topics

urban-planning spatial-planning graph-neural-networks reinforcement-learning

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31 commits on the default branch (main) since jan '22

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The primary language is Jupyter Notebook but there's also others...

updated: 2024-12-03 @ 10:54pm, id: 584252438 / R_kgDOItL8Fg