fix readmes
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@@ -18,5 +18,5 @@ pip install -e .
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- [ACKTR](baselines/acktr)
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- [ACKTR](baselines/acktr)
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- [DDPG](baselines/ddpg)
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- [DDPG](baselines/ddpg)
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- [DQN](baselines/deepq)
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- [DQN](baselines/deepq)
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- [PPO](baselines/pposgd)
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- [PPO](baselines/ppo1)
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- [TRPO](baselines/trpo_mpi)
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- [TRPO](baselines/trpo_mpi)
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@@ -2,6 +2,6 @@
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- Original paper: https://arxiv.org/abs/1707.06347
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- Original paper: https://arxiv.org/abs/1707.06347
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- Baselines blog post: https://blog.openai.com/openai-baselines-ppo/
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- Baselines blog post: https://blog.openai.com/openai-baselines-ppo/
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- `python -m baselines.ppo.run_atari` runs the algorithm for 40M frames = 10M timesteps on an Atari game. See help (`-h`) for more options.
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- `mpirun -np 8 python -m baselines.ppo.run_atari` runs the algorithm for 40M frames = 10M timesteps on an Atari game. See help (`-h`) for more options.
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- `python -m baselines.ppo.run_mujoco` runs the algorithm for 1M frames on a Mujoco environment.
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- `python -m baselines.ppo.run_mujoco` runs the algorithm for 1M frames on a Mujoco environment.
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@@ -2,5 +2,5 @@
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- Original paper: https://arxiv.org/abs/1502.05477
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- Original paper: https://arxiv.org/abs/1502.05477
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- Baselines blog post https://blog.openai.com/openai-baselines-ppo/
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- Baselines blog post https://blog.openai.com/openai-baselines-ppo/
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- `python -m baselines.ppo1.run_atari` runs the algorithm for 40M frames = 10M timesteps on an Atari game. See help (`-h`) for more options.
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- `mpirun -np 16 python -m baselines.ppo1.run_atari` runs the algorithm for 40M frames = 10M timesteps on an Atari game. See help (`-h`) for more options.
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- `python -m baselines.ppo1.run_mujoco` runs the algorithm for 1M timesteps on a Mujoco environment.
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- `python -m baselines.ppo1.run_mujoco` runs the algorithm for 1M timesteps on a Mujoco environment.
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