Genetic algorithm extensions

Abstract

We have developed a genetic algorithm approach for automatically generating procedural textures. Our system, known as GenShade, evaluates evolutionarily generated procedural textures by comparing their rendered images with single or multiple target images of a desired texture. It uses a multiresolution image querying metric to automatically prioritize parents for breeding. GenShade uses a novel approach to the genetic algorithm problem, mimicking several key factors in natural selection. It employs a multiple generation breeding population, a notion of gender, and the concept of aging to maintain diversity while providing many breeding opportunities to highly successful offspring. The approach is also especially efficient running in a multiple processor, multiple selectionstrategy mode. This paper discusses and evaluates these Genetic Algorithm extensions.