I'm trying to understand exactly how to use experience replay in DQN but I'm not sure I understand how it's done.
Here's how I think it develops:
Observe state s Take action a Observe reward r and new state s' Store transition in replay memory D(s,a,r,s')
Now my question is where exactly do we go from here? do we train the network and update the weights here, then on the next transition, instead of training the network on that transition, we sample a random one from the replay memory and update the weights like below?
Update weights take action a observe reward r and new state s' Store new transition in D sample random transition from D (which till now has only 2 entries) Update weights according to sampled transition repeat...
Is this how it's done?