  According to Kant's (1724 -- 1804) philosophical aesthetics, laid down in his
Critique of the Power of Judgement (1790), beauty is "subjective
purposefulness", reflected by the "harmony of the cognitive faculties", which
are "understanding" and "imagination". On the one hand, understanding refers to
the mental capability to find regularities in sensory manifolds, while
imagination refers to intuition, fantasy, and creativity of the mind, on the
other hand. Inspired by the reinforcement learning theory of Schmidhuber, I
present a neural network analogy for the harmony of the faculties in terms of
generative adversarial networks (GAN) - also often employed for artificial
music composition -- by identifying the generator module with the faculty of
imagination and the discriminator module with the faculty of understanding.
According to the GAN algorithm, both modules are engaged in an adversarial
game, thereby optimizing a particular objective function. In my reconstruction,
the convergence of the GAN algorithm during the reception of art, either music
or fine, entails the harmony of the faculties and thereby a neural network
analogue of subjective purposefulness, i.e., beauty.
