To understand one-dimensional continuous fitness landscapes by drift analysis

Abstract

This work shows that we could describe the characteristics of easy and hard fitness landscapes in one-dimensional continuous space by drift analysis. The work expends the existing results in the discrete space into the continue space. A fitness landscape, here, is regarded as the behaviour of an evolutionary algorithm on fitness functions. Based on the drift analysis, easy fitness landscapes are thought to be a "short-distance" landscape, which is easy for the evolutionary algorithm to find the optimal point; and hard fitness landscapes then are as a far-distance landscape, which the evolutionary algorithm had to spend a long time to find the optimal point.