RL is extremely active now and methods are improving considerably, but it’s hard to keep up with research since it’s spread out so much—RL stuff often shows up in places like /r/machinelearning but only intermittently as it’s not the major focus. This is despite RL being one of the most important applications of the deep learning revolution and the single most relevant area to AI risk. I’ve been submitting most of the important papers and news for the past half-year or so, so this might be a useful place to subscribe to.
Thanks for sharing this! I notice the RL subreddit doesn’t have a wiki. I’m very new to ml (on week 6 of Ng’s coursera class), and I’m wondering if there are good shallow overview of RL from the perspective you’re pointing at (i.e. with regards to being a strong application for deep learning and relevance to AI risk).
RL is extremely active now and methods are improving considerably, but it’s hard to keep up with research since it’s spread out so much—RL stuff often shows up in places like /r/machinelearning but only intermittently as it’s not the major focus. This is despite RL being one of the most important applications of the deep learning revolution and the single most relevant area to AI risk. I’ve been submitting most of the important papers and news for the past half-year or so, so this might be a useful place to subscribe to.
Thanks for sharing this! I notice the RL subreddit doesn’t have a wiki. I’m very new to ml (on week 6 of Ng’s coursera class), and I’m wondering if there are good shallow overview of RL from the perspective you’re pointing at (i.e. with regards to being a strong application for deep learning and relevance to AI risk).