Information landscapes and the analysis of search algorithms

Authors:
Borenstein Yossi;Riccardo Poli
Affiliations:
University of Essex;University of Essex
Venue:
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Year:
2005

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Abstract

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.