# Lab 4, SDS 2016

## Homework - RNN DST

• Report bugs
• Come up with a RNN model encoded as Tensorflow computation graph
• Implement it in tracker/GRUmodel.py
• Use RNN for encode inputs from each turn sys_utt + DELIM + user_utt
• For each turn predict the slots based on the last state from the RNN
• This model does in fact more SLU (spoken language understanding) because it does care about history
• If you have this model working start refactoring the code for using encoding dialogue history with another RNN