What is the current state-of-the-art in Reinforcement Learning regarding data efficiency? In other words, which existing reinforcement method learns in fewest episodes? R-Max comes to mind, but its very old and I'd like to know if there is something better now.
There is a very interesting learning agent. They call it Neural-Episodic-Control. Here is the link for the paper: https://arxiv.org/abs/1703.01988 . Their experiments show that NEC requires an order of magnitude fewer interactions with the environment than agents previously proposed.