I think that's a fair point, though I think that semantic meaning is often decided by popular vote. If the masses of undergrads excited about AI have decided th

I think that's a fair point, though I think that semantic meaning is often decided by popular vote. If the masses of undergrads excited about AI have decided that RL == "Deep RL" == DQN, then that's the practical definition one should when discussing RL around the water cooler (for instance, "whether RL works in commercial applications"). I am not really aware of any RL (deep or not) being deployed in commerce besides bandit problems used in recommender systems and the strong similarities between shortest-paths / graph planning. Any thoughts?