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# [pymarl3](https://github.com/tjuHaoXiaotian/pymarl3): the source code of the ICLR-2023 paper `Boosting Multi-Agent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks`
# [pymarl3](https://github.com/tjuHaoXiaotian/pymarl3): the source code of ICLR-2023 paper
**[Boosting Multi-Agent Reinforcement Learning via Permutation Invariant and Permutation Equivariant Networks](https://openreview.net/pdf?id=OxNQXyZK-K8)**.

We extend [**pymarl2**(https://github.com/hijkzzz/pymarl2)](https://github.com/hijkzzz/pymarl2) to **pymarl3**, adding the support for the [SMAC-V2 environment](https://github.com/oxwhirl/smacv2) and equipping the MARL algorithms with permutation invariance and permutation equivariance properties.
We extend [**pymarl2** (https://github.com/hijkzzz/pymarl2)](https://github.com/hijkzzz/pymarl2) to **pymarl3**, adding the support for the [SMAC-V2 environment](https://github.com/oxwhirl/smacv2) and equipping the MARL algorithms with permutation invariance and permutation equivariance properties.

## Key Features:
* (1) **Support both [SMAC-V1](https://github.com/oxwhirl/smac) and [SMAC-V2](https://github.com/oxwhirl/smacv2)** (without the need of installing each environment separately).
* ![SMAC-V2 configs](./doc/figure/smac_v2_config.png)
* (2) Equip the MARL algorithms of [**pymarl2**](https://github.com/hijkzzz/pymarl2) with the **permutation invariance (PI) and permutation equivariance (PE)** properties. The proposed PI and PE model architectures **can be easily plugged into any existing MARL algorithms and boost their performance**.
* (3) :rocket: **The enhanced algorithm achieves State-Of-The-Art (SOTA) performance on SMAC-V1 and SMAC-V2** (without restricting the agent field-of-view and shooting range to a cone).

:rocket: **The enhanced algorithm achieves State-Of-The-Art (SOTA) performance on SMAC-V1 and SMAC-V2** (without restricting the agent field-of-view and shooting range to a cone).

* `[2023-07 update]: Commit the support for SMAC-V2.`
```
[2023-07 update]: Commit the support for SMAC-V2.
```

## 1. Model Architecture of Hyper Policy Network (HPN)

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