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Fixed typo on #092 (#824)

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Darío Hereñú
2019-04-01 19:41:52 -03:00
committed by pzhokhov
parent 58541db226
commit b1644157d6
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README.md
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@@ -89,7 +89,7 @@ python -m baselines.run --alg=ppo2 --env=Humanoid-v2 --network=mlp --num_timeste
will set entropy coefficient to 0.1, and construct fully connected network with 3 layers with 32 hidden units in each, and create a separate network for value function estimation (so that its parameters are not shared with the policy network, but the structure is the same)
See docstrings in [common/models.py](baselines/common/models.py) for description of network parameters for each type of model, and
docstring for [baselines/ppo2/ppo2.py/learn()](baselines/ppo2/ppo2.py#L152) for the description of the ppo2 hyperparamters.
docstring for [baselines/ppo2/ppo2.py/learn()](baselines/ppo2/ppo2.py#L152) for the description of the ppo2 hyperparameters.
### Example 2. DQN on Atari
DQN with Atari is at this point a classics of benchmarks. To run the baselines implementation of DQN on Atari Pong: