> usually post hoc rationalisation built constructively to come to an already held conclusion that "feels right"
Counterfactual reasoning is a promising direction for AI. What would have happened if the situation were slightly different? That means we have a 'world model' in our head and can try our ideas out 'in simulation' before applying them in reality. That's why a human driver doesn't need to crash 1000 times before learning to drive, unlike RL agents. This post hoc rationalisation is our way of grounding intuition to logical models of the world, it's model based RL.
