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KarthikNayaksoumith
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Update reinforcement_q_learning: small grammer fix (#423)
The current explanation is a little confusing and had me read the paragraph twice to understand. _Very_ small change, but should improve readability.
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intermediate_source/reinforcement_q_learning.py

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@@ -344,7 +344,7 @@ def select_action(state):
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steps_done += 1
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if sample > eps_threshold:
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with torch.no_grad():
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# t.max(1) will return largest value for column of each row.
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# t.max(1) will return largest column value of each row.
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# second column on max result is index of where max element was
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# found, so we pick action with the larger expected reward.
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return policy_net(state).max(1)[1].view(1, 1)

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