Abstract
The visual system has different ways to maintain a correct performance; among them, there are optical mechanisms that have evolved to optimize retinal image quality. For example, optical aberrations of the cornea and the crystalline lens partially compensate for each other, giving a complete eye with better quality than either component alone. The purpose of this work is to use evolutionary computing to explore mechanisms of ocular development and how optical parameters of the eye might have evolved. A biologically inspired genetic algorithm was applied to model possible ways of evolution/adaptation of the optics of the cornea and the lens starting from a random population of eyes. Transformations are made by means of standard evolutionary processes (crossover, mutation, and selection) according to the fitness to a metric of image quality. In particular, the evolution of spherical aberration in the eye and the plausible changes in the shape of the different ocular surfaces were investigated.