Information landscapes and the analysis of search algorithms
Yossi Borenstein, Riccardo Poli · 2005
In [15] we introduced the information landscape as a new concept of a landscape. We showed that for a landscape of a small size, information landscape theory can be used to predict the performance of a GA without running the algorithm. Based on this framework, here we develop a new theoretical model to study search algorithms in general. Particularly, we are able to infer important properties of a search algorithm without having knowledge about its specific operators. We give an example of this technique for a simple GA.