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[rllib] [doc] Broken link in ddpg doc

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Eric Liang
2018-05-20 00:10:59 -07:00
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commit f37e2e5d2f
1 changed files with 2 additions and 2 deletions
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doc/source/rllib.rst
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@@ -76,7 +76,7 @@ The ``train.py`` script has a number of options you can show by running
The most important options are for choosing the environment
with ``--env`` (any OpenAI gym environment including ones registered by the user
can be used) and for choosing the algorithm with ``--run``
(available options are ``PPO``, ``PG``, ``A3C``, ``ES``, ``DDPG``, ``DDPG2``, ``DQN``, ``APEX``, and ``APEX_DDPG2``).
(available options are ``PPO``, ``PG``, ``A3C``, ``ES``, ``DDPG``, ``DDPG2``, ``DQN``, ``APEX``, and ``APEX_DDPG``).
Specifying Parameters
~~~~~~~~~~~~~~~~~~~~~
@@ -91,7 +91,7 @@ Each algorithm has specific hyperparameters that can be set with ``--config`` -
`DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg/ddpg.py>`__,
`DDPG2 <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg2/ddpg.py>`__,
`APEX <https://github.com/ray-project/ray/blob/master/python/ray/rllib/dqn/apex.py>`__, and
`APEX_DDPG2 <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg2/apex.py>`__.
`APEX_DDPG <https://github.com/ray-project/ray/blob/master/python/ray/rllib/ddpg/apex.py>`__.
In an example below, we train A3C by specifying 8 workers through the config flag.
function that creates the env to refer to it by name. The contents of the env_config agent config field will be passed to that function to allow the environment to be configured. The return type should be an OpenAI gym.Env. For example: