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"DOM-Q-NET: Grounded RL on Structured Language"International Conference on Learning Representations (2019). Sheng Jia, Jamie Kiros, Jimmy Ba.[arxiv][openreview]

Trained multitask agent:https://www.youtube.com/watch?v=eGzTDIvX4IY
Facebook login:https://www.youtube.com/watch?v=IQytRUKmWhs&t=2s

Need to download selenium & install chrome driver for selenium..

1. Clone this repo
2. Download MiniWoB++ environment from the original repohttps://github.com/stanfordnlp/miniwob-plusplus
   and copy miniwob-plusplus/html folder to miniwob/html in this repo
   
3. In fact, this html folder could be stored anywhere, but remember to perform one of the following actions:
   

• Set environment variable"WOB_PATH" to
  file://"your-path-to-miniwob-plusplus"/html/miniwob
  E.g. "your-path-to-miniwob-plusplus" is "/h/sheng/DOM-Q-NET/miniwob
• Directly modify thebase_url on line 33 of instance.py to
  "your-path-to-miniwob-plusplus"/html/miniwob
  In my case,base_url='file:///h/sheng/DOM-Q-NET/miniwob/html/miniwob/'
  

Experiment launch files are stored underrunsFor example,

cd runs/hard2medium9tasks/sh run1.sh

will launch a 11 multi-task (social-mediasearch-enginelogin-userenter-passwordclick-checkboxesclick-optionenter-dynamic-textenter-textemail-inbox-deleteclick-tab-2navigation-tree) experiment.

• UNKnown tokens
  These are assigned to a random vector such that the cosine distance with the text attribute can yield 1.0 for the direct alignment.

Credit to Dopamine for the implementation of prioritized replay used in dstructs/dopamine_segtree.py