Reinforcement Learning is basically sticks and carrots and the problem is credit assignment. Did I get hit with the stick because I said 5 plus 3 is 8? Or becau

Reinforcement Learning is basically sticks and carrots and the problem is credit assignment. Did I get hit with the stick because I said 5 plus 3 is 8? Or because I wrote my answers in green ink? Or... That used to be what RL was. S&B talk about "modern reinforcement learning" and introduce "Temporal Difference Learning", but imo the book is a bit of a rummage through GOFAI. Is the recent innovation with LLMs to perhaps use feedback to generate prompts? Talking about RL in this context does seem to be an attempt to freshen up interest. "Look! LLMs version 4.0! Now with added Science!"