Multiple Objective Vector-Based Genetic Programming Using Human-Derived Primitives
Jason Zutty, Daniel Zhuoyu Long, Heyward Adams, Gisele Bennett, Christina M. Baxter · 2015
Traditional genetic programming only supports the use of arithmetic and logical operators on scalar features. The GTMOEP (Georgia Tech Multiple Objective Evolutionary Programming) framework builds upon this by also handling feature vectors, allowing the use of signal processing and machine learning functions as primitives, in addition to the more conventional operators. GTMOEP is a novel method for automated, data-driven algorithm creation, capable of outperforming human derived solutions.