semvec/pypi-packages huggingface dataset:
pyg-multiagent 0.0.5
Python Package for Multi-Agent Learning
Requires Python: >=3.8
Keywords: deep-learning,pytorch,geometric-deep-learning,graph-neural-networks,pytorch-geometric,multi-agent

![logo](https://raw.githubusercontent.com/rainorangelemon/pygma_sphinx_theme/master/pygma_sphinx_theme/static/img/text_logo.png)

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**[Documentation](https://pytorch-geometric-multiagent.readthedocs.io/en/latest/)**

The official repo for the CoRL 2022 paper 'Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation' [[project page](https://rainorangelemon.github.io/CoRL2022/)]

<!--The current repo only includes GNN for control. For planning methods such as CBS and SIPP, please stay tuned.-->

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

```bash
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
```
deucalion 0.0.1
Deucalion: Edge anomaly detection framework based on Prometheus monitoring.
Requires Python: >=3.7,<4.0
Keywords: deucalion,anomaly detection,prometheus,kubernetes,microservices

# Deucalion: Edge anomaly detection framework based on Prometheus

## Surviving the flood of monitoring data

This repository is a monorepo containing:
- The Deucalion Python library
- A boilerplate Deucalion application
- Helm deployment charts
- Evaluation setup