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Update rl_intro2.rst #385

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2 changes: 1 addition & 1 deletion docs/spinningup/rl_intro2.rst
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Expand Up @@ -100,7 +100,7 @@ Unlike model-free RL, there aren't a small number of easy-to-define clusters of
* The `ExIt`_ algorithm uses this approach to train deep neural networks to play Hex.
* `AlphaZero`_ is another example of this approach.

**Data Augmentation for Model-Free Methods.** Use a model-free RL algorithm to train a policy or Q-function, but either 1) augment real experiences with fictitious ones in updating the agent, or 2) use *only* fictitous experience for updating the agent.
**Data Augmentation for Model-Free Methods.** Use a model-free RL algorithm to train a policy or Q-function, but either 1) augment real experiences with fictitious ones in updating the agent, or 2) use *only* fictitious experience for updating the agent.

* See `MBVE`_ for an example of augmenting real experiences with fictitious ones.
* See `World Models`_ for an example of using purely fictitious experience to train the agent, which they call "training in the dream."
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