An Introduction to Semi-supervised Reinforcement Learning

As usual, our goal is to quickly learn a policy which receives a high reward per episode. We can apply a traditional RL algorithm to the semi-supervised setting by simply ignoring all of the unlabelled episodes. This will generally result in very slow learning. The interesting challenge is to learn efficiently from the unlabelled episodes. I think that semi-supervised RL is a valuable ingredient for AI control, as well as an interesting research problem in reinforcement learning.