Seven Pillars of Causal Reasoning with Reflections on Machine Learning [pdf]
I'm surprised Pearl doesn't mention reinforcement learning once in this essay. This domain is where Pearl-style causal reasoning frameworks most closely meets data-driven statistical machine learning methods. Methods such have Dyna (link below) can be seen as reinforcement learning with some degree of "reasoning" about future consequences of actions. I suspect that there is more work to be done in embedding causal methods into planning, though it's pretty clear that a lot of progress is being made in domains such as Atari.<p>Dyna:
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