Update docs about recoving original envs

mo_gymnasium/envs/mujoco/half_cheetah_v5.py

@@ -13,7 +13,7 @@ class MOHalfCheehtahEnv(HalfCheetahEnv, EzPickle):
 
     The original Gymnasium's 'HalfCheetah-v5' is recovered by the following linear scalarization:
 
-    env = mo_gym.make('mo-halfcheetah-v4')
+    env = mo_gym.make('mo-halfcheetah-v5')
     LinearReward(env, weight=np.array([1.0, 0.1]))
 
     ## Reward Space

mo_gymnasium/envs/mujoco/hopper_v5.py

@@ -11,6 +11,11 @@ class MOHopperEnv(HopperEnv, EzPickle):
 
     See [Gymnasium's env](https://gymnasium.farama.org/environments/mujoco/hopper/) for more information.
 
+    The original Gymnasium's 'Hopper-v5' is recovered by the following linear scalarization:
+
+    env = mo_gym.make('mo-hopper-v5')
+    LinearReward(env, weight=np.array([1.0, 0.0, 1e-3]))
+
     ## Reward Space
     The reward is 3-dimensional:
     - 0: Reward for going forward on the x-axis

mo_gymnasium/envs/mujoco/humanoid_v5.py

@@ -11,6 +11,11 @@ class MOHumanoidEnv(HumanoidEnv, EzPickle):
 
     See [Gymnasium's env](https://gymnasium.farama.org/environments/mujoco/humanoid/) for more information.
 
+    The original Gymnasium's 'Humanoid-v5' is recovered by the following linear scalarization:
+
+    env = mo_gym.make('mo-humanoid-v5')
+    LinearReward(env, weight=np.array([1.25, 0.1]))
+
     ## Reward Space
     The reward is 2-dimensional:
     - 0: Reward for running forward (x-velocity)

mo_gymnasium/envs/mujoco/swimmer_v5.py

@@ -11,9 +11,9 @@ class MOSwimmerEnv(SwimmerEnv, EzPickle):
 
     See [Gymnasium's env](https://gymnasium.farama.org/environments/mujoco/swimmer/) for more information.
 
-    The original Gymnasium's 'Swimmer-v4' is recovered by the following linear scalarization:
+    The original Gymnasium's 'Swimmer-v5' is recovered by the following linear scalarization:
 
-    env = mo_gym.make('mo-swimmer-v4')
+    env = mo_gym.make('mo-swimmer-v5')
     LinearReward(env, weight=np.array([1.0, 1e-4]))
 
     ## Reward Space

mo_gymnasium/envs/mujoco/walker2d_v5.py

@@ -11,6 +11,11 @@ class MOWalker2dEnv(Walker2dEnv, EzPickle):
 
     See [Gymnasium's env](https://gymnasium.farama.org/environments/mujoco/walker2d/) for more information.
 
+    The original Gymnasium's 'Walker2d-v5' is recovered by the following linear scalarization:
+
+    env = mo_gym.make('mo-walker2d-v5')
+    LinearReward(env, weight=np.array([1.0, 1e-3]))
+
     ## Reward Space
     The reward is 2-dimensional:
     - 0: Reward for running forward (x-velocity)