The emergence and distribution of species in a gradient-based spatially-structured evolutionary algorithm
The ability to discover and maintain multiple solutions within a single run is a desirable property for evolutionary algorithms. Researchers have previously turned to many biologically-inspired methods for inspiration to produce niching evolutionary algorithms. This paper extends previous work on the Gradient-Based Spatially-Structured Evolutionary Algorithm, which attempts to embody the concept of parapatric speciation within an evolutionary algorithm. Through an comparison of the evolved population with that of an idealised, perfectly proportioned population, we show that the distribution of population members among the niches of a given problem’s ﬁtness landscape does not rely on the global properties of the landscape. Rather, the allocation of individuals to peaks relies on the relative values of neighbouring peaks with regard to their spatial relationship in the ﬁtness landscape.
Conference: 19th Annual Colloquium of the Spatial Information Research Centre (SIRC 2007: Does Space Matter?), Dunedin, New Zealand
Keywords: population structure; niching methods; environmental gradients; Evolutionary Algorithms
Research Type: Conference or Workshop Item (Paper)