Connecting Automatic Parameter Tuning, Genetic Programming as a Hyper-heuristic, and Genetic Improvement Programming

Automatically designing algorithms has long been a dream of computer scientists. Early attempts which generate computer programs from scratch, have failed to meet this goal. However, in recent years there have been a number of different technologies with an alternative goal of taking existing programs and attempting to improving them. These methods form a range of methodologies, from the "limited" ability to change (for example only the parameters) to the "complete" ability to change the whole program. These include; automatic parameter tuning (APT), using GP as a hyper-heuristic (GPHH), and GI, which we will now briefly review. Part of research is building links between existing work, and the aim of this paper is to bring together these currently separate approaches.