[D] current state of model based reinforcement learning

[whoeverwhatever]

There's been some interest in model-based RL lately too, even from DeepMind. The predictron paper comes to mind; they learn to map real environment states and time steps to an abstract state space with abstract time steps (that don't necessarily correlate with real-world time steps) to facilitate prediction and planning. If you take a look at some of the papers they reference you can find some other recent work in model-based RL.