In the past, I was very skeptical of NLP efforts. Thought it was mostly full of cool toys.
I was dead wrong.
I am similarly skeptical of RL, in the sense that for most cases you are better of using optimal control techniques, and maybe sometimes a combination of RL and optimal control.
I am aware of AlphaZero and other impressive achievements in certain games. However, I am still left with the feeling that it is very expensive to train an RL model and it is insanely specific to the task at hand.
Are there recent breakthroughs that point at promising generalization in the RL community?
Breakthrough may well be among the recent reformulations into supervised, offline RL and related techniques.
Of special interest, the decision transformer and the very emerging litterature on diffusion planning.
This is a more up to date version of David Silver’s course and judging from the few lectures I watched, it is very good but if you haven’t, I recommend having a look at Silver’s lectures, too. He is an amazing teacher and it is a joy to watch him explain something. https://www.deepmind.com/learning-resources/introduction-to-...
I was dead wrong.
I am similarly skeptical of RL, in the sense that for most cases you are better of using optimal control techniques, and maybe sometimes a combination of RL and optimal control.
I am aware of AlphaZero and other impressive achievements in certain games. However, I am still left with the feeling that it is very expensive to train an RL model and it is insanely specific to the task at hand.
Are there recent breakthroughs that point at promising generalization in the RL community?