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facebookresearch · Nov 24, 2024 · 62bfcb6 · 62bfcb6
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diff --git a/README.md b/README.md
@@ -239,13 +239,14 @@ determine the training strategy. Here is a table with the currently implemented
 challenge to solve.
 They differ based on many aspects, here is a table with the current environments in BenchMARL
 
-| Environment                                                        | Tasks                                | Cooperation               | Global state | Reward function               | Action space          |    Vectorized    |
-|--------------------------------------------------------------------|--------------------------------------|---------------------------|--------------|-------------------------------|-----------------------|:----------------:|
-| [VMAS](https://github.com/proroklab/VectorizedMultiAgentSimulator) | [27](benchmarl/conf/task/vmas)       | Cooperative + Competitive | No           | Shared + Independent + Global | Continuous + Discrete |       Yes        |    
-| [SMACv2](https://github.com/oxwhirl/smacv2)                        | [15](benchmarl/conf/task/smacv2)     | Cooperative               | Yes          | Global                        | Discrete              |        No        |
-| [MPE](https://github.com/openai/multiagent-particle-envs)          | [8](benchmarl/conf/task/pettingzoo)  | Cooperative + Competitive | Yes          | Shared + Independent          | Continuous + Discrete |        No        |
-| [SISL](https://github.com/sisl/MADRL)                              | [2](benchmarl/conf/task/pettingzoo)  | Cooperative               | No           | Shared                        | Continuous            |        No        |
-| [MeltingPot](https://github.com/google-deepmind/meltingpot)        | [49](benchmarl/conf/task/meltingpot) | Cooperative + Competitive | Yes          | Independent                   | Discrete              |        No        |
+| Environment                                                         | Tasks                                | Cooperation               | Global state | Reward function               | Action space          |    Vectorized    |
+|---------------------------------------------------------------------|--------------------------------------|---------------------------|--------------|-------------------------------|-----------------------|:----------------:|
+| [VMAS](https://github.com/proroklab/VectorizedMultiAgentSimulator)  | [27](benchmarl/conf/task/vmas)       | Cooperative + Competitive | No           | Shared + Independent + Global | Continuous + Discrete |       Yes        |    
+| [SMACv2](https://github.com/oxwhirl/smacv2)                         | [15](benchmarl/conf/task/smacv2)     | Cooperative               | Yes          | Global                        | Discrete              |        No        |
+| [MPE](https://github.com/openai/multiagent-particle-envs)           | [8](benchmarl/conf/task/pettingzoo)  | Cooperative + Competitive | Yes          | Shared + Independent          | Continuous + Discrete |        No        |
+| [SISL](https://github.com/sisl/MADRL)                               | [2](benchmarl/conf/task/pettingzoo)  | Cooperative               | No           | Shared                        | Continuous            |        No        |
+| [MeltingPot](https://github.com/google-deepmind/meltingpot)         | [49](benchmarl/conf/task/meltingpot) | Cooperative + Competitive | Yes          | Independent                   | Discrete              |        No        |
+| [MAgent2](https://github.com/Farama-Foundation/magent2)             | [1](benchmarl/conf/task/magent)      | Cooperative + Competitive | Yes          | Global in groups              | Discrete              |        No        |
 
 
 > [!NOTE]  

diff --git a/benchmarl/environments/magent/common.py b/benchmarl/environments/magent/common.py
@@ -25,11 +25,11 @@ class MAgentTask(Task):
     # TIGER_DEER = None
 
     def get_env_fun(
-            self,
-            num_envs: int,
-            continuous_actions: bool,
-            seed: Optional[int],
-            device: DEVICE_TYPING,
+        self,
+        num_envs: int,
+        continuous_actions: bool,
+        seed: Optional[int],
+        device: DEVICE_TYPING,
     ) -> Callable[[], EnvBase]:
 
         return lambda: PettingZooWrapper(
@@ -38,7 +38,7 @@ def get_env_fun(
             seed=seed,
             done_on_any=False,
             use_mask=False,
-            device=device
+            device=device,
         )
 
     def __get_env(self) -> EnvBase:
@@ -51,8 +51,10 @@ def __get_env(self) -> EnvBase:
                 # gather_v5,
                 # tiger_deer_v4
             )
-        except ImportError as e:
-            raise ImportError("Module `magent2` not found, install it using `pip install magent2`")
+        except ImportError:
+            raise ImportError(
+                "Module `magent2` not found, install it using `pip install magent2`"
+            )
 
         envs = {
             "ADVERSARIAL_PURSUIT": adversarial_pursuit_v4,

diff --git a/docs/source/concepts/components.rst b/docs/source/concepts/components.rst
@@ -91,6 +91,8 @@ They differ based on many aspects, here is a table with the current environments
     +-------------------------------------------------+-------+---------------------------+--------------+-------------------------------+-----------------------+------------+
     | :class:`~benchmarl.environments.MeltingPotTask` |  49   | Cooperative + Competitive |     Yes      |          Independent          |       Discrete        |     No     |
     +-------------------------------------------------+-------+---------------------------+--------------+-------------------------------+-----------------------+------------+
+    | :class:`~benchmarl.environments.MAgentTask`     |  1    | Cooperative + Competitive |     Yes      |          Global in groups     |       Discrete        |     No     |
+    +-------------------------------------------------+-------+---------------------------+--------------+-------------------------------+-----------------------+------------+