# huangwl18/modular-rl

<https://repo.masters-masters.com/en/repos/huangwl18/modular-rl>

[Home](https://repo.masters-masters.com/en) › [huangwl18](https://repo.masters-masters.com/en/owners/huangwl18) › [modular-rl](https://repo.masters-masters.com/en/repos/huangwl18/modular-rl)

huangwl18/modular-rl has 234 stars on GitHub. Its RepoMasters card: Prototype tier. \[ICML 2020\] PyTorch Code for "One Policy to Control Them All: Shared…

| Field | Value |
| --- | --- |
| Owner | [huangwl18](https://repo.masters-masters.com/en/owners/huangwl18) |
| Stars | 234 |
| Forks | 34 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2020 |
| Topics | deep-learning, reinforcement-learning, modularity, graph-neural-networks, locomotion, generalization, modular-control, decentralized-control, message-passing, emergent-communication |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [huangwl18/modular-rl](https://github.com/huangwl18/modular-rl) |

## Repository

\[ICML 2020\] PyTorch Code for "One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control"

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.