Thanks to Tim Tyler and James Bowery's explanations 👍

My idea is just a general learning algorithm that can be applied to both
supervised and unsupervised situations.

I am focusing on how to learn logic rules efficiently.  The logic rules
would explain a set of data (such data is also expressed as logic
formulas), this seems to fall into the unsupervised category.  But the
fitness function of the genetic algorithm can really be anything desired.

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