<issue_start><issue_comment>Title: Off-line training
username_0: In some cases, Deep-RL algorithms take way too much time to learn on-line. It would be great to be able to first use controllers and exploration algorithms to save the experience, and then use that data to train/evaluate the agents.

My view right now is that the simplest way would be to:
- save all the time-steps using the Logger (when `Log-Freq==0`)
- change `SimionApp::run()` so that it uses a flag to switch between off-line/on-line learning
<issue_comment>username_0: New tool added (_SimionLogToOfflineTraining_) that takes a folder as input and outputs a single file with `numTuples` tuples `<s,a,s_p,r>` sampled from all the log files in the input folder.
<issue_comment>username_0: The sample file might be too big to store in memory. I think we need to read it in chunks<issue_closed>