In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the DRQN is described as DQN with the first post-convolutional fully-connected layer replaced by a recurrent LSTM.
I have DQN implementation with only two dense layers. I want to change this into DRQN with the first layer as an LSTM and leave the second dense layer untouched. If I understood correctly, I would also need to change the input data appropriately.
Are there any other things that need to be modified in order to make DRQN work?
