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docs for rl example
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docs/user/example.rst

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@@ -44,10 +44,10 @@ Adversarial Learning
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Reinforcement Learning
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==============================
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- Policy Gradient / Network - Pong Game. Teach a machine to play Pong games, see `tutorial_atari_pong.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py>`_.
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- Policy Gradient / Network - Atari Ping Pong, see `tutorial_atari_pong.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py>`_.
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- Deep Q-Network - Frozen lake, see `tutorial_frozenlake_dqn.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py>`_.
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- Q-Table learning algorithm - Frozen lake, see `tutorial_frozenlake_q_table.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_q_table.py>`_.
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- Asynchronous Policy Gradient using TensorDB - Pong Game by `nebulaV <https://github.com/akaraspt/tl_paper>`_.
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- Asynchronous Policy Gradient using TensorDB - Atari Ping Pong by `nebulaV <https://github.com/akaraspt/tl_paper>`_.
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- A3C for continuous action space - Bipedal Walker, see `tutorial_bipedalwalker_a3c*.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_bipedalwalker_a3c_continuous_action.py>`_.
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