[rllib] Fix broken link in docs (ray-project#1967)

* Update README.rst * Update rllib.rst
Emily0219 · Apr 30, 2018 · b55f4a7 · b55f4a7
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diff --git a/doc/source/rllib.rst b/doc/source/rllib.rst
@@ -17,7 +17,7 @@ RLlib's policy optimizers serve as the basis for RLlib's reference algorithms, w
 
 - Deep Deterministic Policy Gradients (`DDPG <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ddpg>`__, `DDPG2 <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ddpg2>`__).
 
-- Ape-X Distributed Prioritized Experience Replay, including both `DQN <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__ and `DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg2/apex.py>`__ variants.
+- Ape-X Distributed Prioritized Experience Replay, including both `DQN <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__ and `DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg/apex.py>`__ variants.
 
 - Evolution Strategies (`ES <https://github.com/ray-project/ray/tree/master/python/ray/rllib/es>`__), as described in `this paper <https://arxiv.org/abs/1703.03864>`__.
 

diff --git a/python/ray/rllib/README.rst b/python/ray/rllib/README.rst
@@ -15,9 +15,8 @@ RLlib includes the following reference algorithms:
 
 - Deep Deterministic Policy Gradients (`DDPG <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ddpg>`__, `DDPG2 <https://github.com/ray-project/ray/tree/master/python/ray/rllib/ddpg2>`__).
 
-- Ape-X Distributed Prioritized Experience Replay, including both `DQN <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__ and `DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg2/apex.py>`__ variants.
+- Ape-X Distributed Prioritized Experience Replay, including both `DQN <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__ and `DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg/apex.py>`__ variants.
 
-- Evolution Strategies (`ES <https://github.com/ray-project/ray/tree/master/python/ray/rllib/es>`__), as described in `this
-   paper <https://arxiv.org/abs/1703.03864>`__.
+- Evolution Strategies (`ES <https://github.com/ray-project/ray/tree/master/python/ray/rllib/es>`__), as described in `this paper <https://arxiv.org/abs/1703.03864>`__.
 
 These algorithms can be run on any OpenAI Gym MDP, including custom ones written and registered by the user.