Wow, thank you for the answer and the links. I had tried to search for something like this but I didn't have the right terminology.
I really hope to see something happen in this area before I die, just for the sake of seeing it happen.
I often wonder about whether neural networks might need to meet at a crossroads with other techniques.
Inductive Logic/Answer Set Programming or Constraints Programming seems like it could be a good match for this field. Because from my ignorant understanding, you have a more "concrete" representation of a model/problem in the form of symbolic logic or constraints and an entirely abstract "black box" solver with neural networks. I have no real clue, but it seems like they could be synergistic?
There's a really oddball repo I found that took this approach:
I really hope to see something happen in this area before I die, just for the sake of seeing it happen.
I often wonder about whether neural networks might need to meet at a crossroads with other techniques.
Inductive Logic/Answer Set Programming or Constraints Programming seems like it could be a good match for this field. Because from my ignorant understanding, you have a more "concrete" representation of a model/problem in the form of symbolic logic or constraints and an entirely abstract "black box" solver with neural networks. I have no real clue, but it seems like they could be synergistic?
There's a really oddball repo I found that took this approach:
https://github.com/921kiyo/symbolic-rl
"Symbolic Reinforcement Learning using Inductive Logic Programming"