Increasing the Throughput of Expensive Evaluations Through a Vector Based Genetic Programming Framework
Jason Zutty, Daniel Long, Gregory Rohling · 2016
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 [6]. GTMOEP is a novel method for automated, data-driven algorithm creation, capable of outperforming human derived solutions.