Probing for limits to building block mixing with a tunably-difficult problem for genetic programming

This paper describes a tunably-difficult problem for genetic programming (GP) that probes for limits to building block mixing and assembly. The existence of such a problem can be used to garner insight into the dynamics of what happens during the course of a GP run. The results indicate that the amount of mixing is fairly low in comparison to the amount of content that could be present in an initial population. Categories and Subject Descriptors I.2.2 [Artificial Intelligence]: Automatic Programming – program synthesis. General Terms Algorithms, Performance, Experimentation, Theory. Keywords Tunably-difficult problems, Highlander problem, building blocks, initial populations.

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Jason M. Daida, Michael E. Samples, Matthew J. Byom
• Keywords: Building Blocks, GECCO 2005, Initial Populations, Tunably-difficult Problems