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Zhao et al.'s model develops both disparity selection and vergence control in an effort to minimize reconstruction error.

It uses a form of sparse-coding to learn to approximate its input and a variation of the actor-critic learning algorithm called natural actor critic reinforcement learning algorithm (NACREL).

The teaching signal to the NACREL algorithm is the reconstruction error of the model after the action produced by it.