Reinforcement Learning Toolbox - When does algorithm train?

2019 9 17
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I am currently using the RL-Toolbox with a DQN-Agent built into a long-running process-simulation.
The maximum stepcount is currently 8000 steps per episode.
Unfortunately the documentation seems a little ambiguous to me, so here my question:
Doese the train-function of the RL-Toolbox train the agent at the end of an episode or during the episode when the step count exeeds the minibatch-size (like in the baseline algorithms)?
Thank you in advance.

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The implementation is based on the algorithm listed here.
Weights are being updated at each time step.

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"For each training time step" - that was the line I was looking for (yet looking into the source code lead me to the same conclusion).
After double-checking the baseline-algorithms I found that they do it the same way.
Thank you for your time!

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