[Docs] Pointers to BenchMARL (pytorch#1710)

ai4co · Jan 9, 2024 · 58571f0 · 58571f0
1 parent 6c68f7e
commit 58571f0
Show file tree

Hide file tree

Showing 2 changed files with 12 additions and 0 deletions.
diff --git a/examples/multiagent/README.md b/examples/multiagent/README.md
@@ -10,6 +10,11 @@ In this folder we provide a set of multi-agent example scripts using the [VMAS](
 
 For more details on the experiment setup and the environments please refer to the corresponding section of the appendix in the [TorchRL paper](https://arxiv.org/abs/2306.00577).
 
+> [!NOTE]  
+> If you are interested in Multi-Agent Reinforcement Learning (MARL) in TorchRL, check out [BenchMARL](https://github.com/facebookresearch/BenchMARL):
+> a benchmarking library where you 
+> can train and compare MARL algorithms, tasks, and models using TorchRL!
+
 ## Using the scripts
 
 ### Install

diff --git a/tutorials/sphinx-tutorials/multiagent_ppo.py b/tutorials/sphinx-tutorials/multiagent_ppo.py
@@ -4,6 +4,13 @@
 ===============================================================
 **Author**: `Matteo Bettini <https://github.com/matteobettini>`_
 
+.. note::
+
+   If you are interested in Multi-Agent Reinforcement Learning (MARL) in
+   TorchRL, check out
+   `BenchMARL <https://github.com/facebookresearch/BenchMARL>`__: a benchmarking library where you
+   can train and compare MARL algorithms, tasks, and models using TorchRL!
+
 This tutorial demonstrates how to use PyTorch and :py:mod:`torchrl` to
 solve a Multi-Agent Reinforcement Learning (MARL) problem.