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@@ -190,6 +190,7 @@ example environments are included in the provided config file.
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| init_entcoef | How much the agent should explore in the beginning of training. | SAC |
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| lambd | The regularization parameter. | PPO |
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| learning_rate | The initial learning rate for gradient descent. | PPO, SAC |
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| learning_rate_schedule | Determines how learning rate changes over time. | PPO, SAC |
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| max_steps | The maximum number of simulation steps to run during a training session. | PPO, SAC |
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| memory_size | The size of the memory an agent must keep. Used for training with a recurrent neural network. See [Using Recurrent Neural Networks](Feature-Memory.md). | PPO, SAC |
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