Interpretable Model-Based Hierarchical RL Using Inductive Logic Programming
I don&#x27;t work in the field, but I sort of passively follow it.<p>A year ago I made this comment, in another ML thread:<p><a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=23315739" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=23315739</a><p><pre><code>  &quot;I often wonder about whether neural networks might need to meet at a crossroads with other techniques.&quot;

  &quot;Inductive Logic&#x2F;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 &quot;concrete&quot; representation of a model&#x2F;problem in the form of symbolic logic or constraints and an entirely abstract &quot;black box&quot; solver with neural networks. I have no real clue, but it seems like they could be synergistic?&quot;
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I can&#x27;t interpret the paper -- is this roughly in this vein?