[Doc] Fix doc lint (ray-project#48669)

Signed-off-by: dentiny <dentinyhao@gmail.com>

rllib/README.rst

@@ -9,7 +9,7 @@ Whether you would like to train your agents in **multi-agent** setups,
 purely from **offline** (historic) datasets, or using **externally
 connected simulators**, RLlib offers simple solutions for your decision making needs.
 
-If you either have your problem coded (in python) as an 
+If you either have your problem coded (in python) as an
 `RL environment <https://docs.ray.io/en/master/rllib/rllib-env.html#configuring-environments>`_
 or own lots of pre-recorded, historic behavioral data to learn from, you will be
 up and running in only a few days.
@@ -50,16 +50,16 @@ Algorithms Supported
 
 Model-free On-policy RL:
 
-- `Synchronous Proximal Policy Optimization (APPO) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#appo>`__ 
+- `Synchronous Proximal Policy Optimization (APPO) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#appo>`__
 - `Proximal Policy Optimization (PPO) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#ppo>`__
-- `Importance Weighted Actor-Learner Architecture (IMPALA) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#impala>`__   
+- `Importance Weighted Actor-Learner Architecture (IMPALA) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#impala>`__
 
 Model-free Off-policy RL:
 
 - `Deep Q Networks (DQN, Rainbow, Parametric DQN) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#dqn>`__
 - `Soft Actor Critic (SAC) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#sac>`__
 
-Model-based RL: 
+Model-based RL:
 
 - `DreamerV3 <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#dreamerv3>`__
 
@@ -69,16 +69,16 @@ Offline RL:
 - `Conservative Q-Learning (CQL) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#cql>`__
 - `Monotonic Advantage Re-Weighted Imitation Learning (MARWIL) <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#marwil>`__
 
-Multi-agent:  
+Multi-agent:
 
-- `Parameter Sharing <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#parameter>`__ 
+- `Parameter Sharing <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#parameter>`__
 - `Shared Critic Methods <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#sc>`__
 
-Others:  
+Others:
 
 - `Fully Independent Learning <https://docs.ray.io/en/master/rllib/rllib-algorithms.html#fil>`__
 
-A list of all the algorithms can be found `here <https://docs.ray.io/en/master/rllib/rllib-algorithms.html>`__ .  
+A list of all the algorithms can be found `here <https://docs.ray.io/en/master/rllib/rllib-algorithms.html>`__ .
 
 
 Quick First Experiment