Fix render_mode in documentation

This replaces gym's old render(mode=...) interface

docs/source/multi_agent.rst

@@ -21,15 +21,15 @@ To that end, update the :ref:`environment configuration <Configuring an environm
 
   import gymnasium as gym
 
-  env = gym.make('highway-v0')
+  env = gym.make('highway-v0', render_mode='rgb_array')
 
   env.configure({"controlled_vehicles": 2})  # Two controlled vehicles
   env.configure({"vehicles_count": 1})  # A single other vehicle, for the sake of visualisation
   env.reset(seed=0)
 
   from matplotlib import pyplot as plt
   %matplotlib inline
-  plt.imshow(env.render(mode="rgb_array"))
+  plt.imshow(env.render())
   plt.title("Controlled vehicles are in green")
   plt.show()
 
@@ -53,14 +53,14 @@ The type of actions contained in the tuple must be described by a standard :ref:
   env.reset()
 
   _, (ax1, ax2) = plt.subplots(nrows=2)
-  ax1.imshow(env.render(mode="rgb_array"))
+  ax1.imshow(env.render())
   ax1.set_title("Initial state")
 
   # Make the first vehicle change to the left lane, and the second one to the right
   action_1, action_2 = 0, 2  # See highway_env.envs.common.action.DiscreteMetaAction.ACTIONS_ALL
   env.step((action_1, action_2))
 
-  ax2.imshow(env.render(mode="rgb_array"))
+  ax2.imshow(env.render())
   ax2.set_title("After sending actions to each vehicle")
   plt.show()
 

docs/source/quickstart.rst

@@ -22,14 +22,14 @@ Here is a quick example of how to create an environment:
   from matplotlib import pyplot as plt
   %matplotlib inline
 
-  env = gym.make('highway-v0')
+  env = gym.make('highway-v0', render_mode='rgb_array')
   env.reset()
   for _ in range(3):
       action = env.action_type.actions_indexes["IDLE"]
       obs, reward, done, truncated, info = env.step(action)
       env.render()
 
-  plt.imshow(env.render(mode="rgb_array"))
+  plt.imshow(env.render())
   plt.show()
 
 All the environments
@@ -70,7 +70,7 @@ For example, the number of lanes can be changed with:
 
   env.config["lanes_count"] = 2
   env.reset()
-  plt.imshow(env.render(mode="rgb_array"))
+  plt.imshow(env.render())
   plt.show()
 
 .. note::