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@@ -24,6 +24,7 @@ We support and test for Python 3.8, 3.9, 3.10 and 3.11 on Linux and macOS. We wi
 
 * [Fetch](https://robotics.farama.org/envs/fetch/) - A collection of environments with a 7-DoF robot arm that has to perform manipulation tasks such as Reach, Push, Slide or Pick and Place.
 * [Shadow Dexterous Hand](https://robotics.farama.org/envs/shadow_dexterous_hand/) - A collection of environments with a 24-DoF anthropomorphic robotic hand that has to perform object manipulation tasks with a cube, egg-object, or pen. There are variations of these environments that also include data from 92 touch sensors in the observation space.
+* [MaMuJoCo](https://robotics.farama.org/envs/MaMuJoCo/) - A collection of multi agent factorizations of the [Gymnasium/MuJoCo](https://gymnasium.farama.org/environments/mujoco/) environments and a framework for factorizing robotic environments, uses the [pettingzoo.ParallelEnv](https://pettingzoo.farama.org/api/parallel/) API. 
 
 The [D4RL](https://github.com/Farama-Foundation/D4RL) environments are now available. These environments have been refactored and may not have the same action/observation spaces as the original, please read their documentation:
 
@@ -32,8 +33,6 @@ The [D4RL](https://github.com/Farama-Foundation/D4RL) environments are now avail
 The different tasks involve hammering a nail, opening a door, twirling a pen, or picking up and moving a ball.
 * [Franka Kitchen](https://robotics.farama.org/envs/franka_kitchen/) - Multitask environment in which a 9-DoF Franka robot is placed in a kitchen containing several common household items. The goal of each task is to interact with the items in order to reach a desired goal configuration.
 
-* [MaMuJoCo](https://robotics.farama.org/envs/MaMuJoCo/) - A collection of multi agent factorizations of the [Gymnasium/MuJoCo](https://gymnasium.farama.org/environments/mujoco/) environments and a framework for factorizing robotic environments, uses the [pettingzoo.ParallelEnv](https://pettingzoo.farama.org/api/parallel/) API. 
-
 **WIP**: generate new `D4RL` environment datasets with [Minari](https://github.com/Farama-Foundation/Minari).
 
 ## Multi-goal API