The official repo for the CoRL 2022 paper 'Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation' [project page]
The ultimate goal is to provide a benchmark and a handy tool for GNN researchers to conduct evaluations properly and fairly for multi-agent tasks.
Note: The current repo is actively under maintenance.
Installation
conda create -n pygma python=3.8
conda activate pygma
# install pytorch, modify the following line according to your environment
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
# install torch geometric, refer to https://github.com/pyg-team/pytorch_geometric
conda install pyg -c pyg
# install pyg_multiagent
pip install pyg_multiagent
Release files for pyg-multiagent 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyg_multiagent-0.0.5.tar.gz | 65.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyg_multiagent-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 299.4 kB
Release files / pyg_multiagent-0.0.5.tar.gz
| Download URL | pyg_multiagent-0.0.5.tar.gz |
|---|---|
| Size | 65.2 kB |
| Tags | Source |
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Release files / pyg_multiagent-0.0.5-py3-none-any.whl
| Download URL | pyg_multiagent-0.0.5-py3-none-any.whl |
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| Size | 234.2 kB |
| Tags | Python 3 |
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