# Parallel Q-learning

I'm looking for academic papers or other credible sources focusing on the topic of parralelized reinforcement learning, specifically Q-learning. I'm mostly interested in methods of sharing Q-table between processes (or joining/syncing them together if each process have it's own). I'd also appreciate a brief description of method used in linked/mentioned sources.

My question is how to parallelize Q-learning which uses neural network as Q-table approximation. I'm looking for credible sources.

I should mention that I use neural network (PyBrain) as approximation.

• Finally, since you asked for DQN, GORILA paper which separates actors, learners and the main node which stores the weights (in tensorflow setting it's called parameter server). As far as I get it, this paper inspired IMPALA.