Reviews: Multi-View Reinforcement Learning

Originality: Considering that multi-view and multi-modal RL papers tend to offer ad-hoc solutions to the problem, this paper's formalization is a nice contribution. Quality & Clarity: The paper is well presented, the math is mostly clear, although some parts aren't obviously translatable to an implementation. In terms of experiments, it seems that many details are lacking, and as far as I call tell, all figures represent a single run of each setting, which is worrisome. Significance: While the contributed framework does seem like a useful formalism, this paper fails to convince me that it actually is: - The proposed experiment in 4.1 creates artificial views which don't seem representative of multimodal settings, in that they all contain the same *information*. It would have been more convincing to feature an experiment where views are truly independent when conditioned on the current state (e.g.