Investigating the success of spatial coevolution

We investigate the results of coevolution of spatially distributed populations. In particular, we describe work in which a simple function approximation problem is used to compare different spatial evolutionary methods. Our work shows that, on this problem, spatial coevolution is dramatically more successful than any other spatial evolutionary scheme we tested. Our results support two hypotheses about the source of spatial coevolution’s superior performance: (1) spatial coevolution allows population diversity to persist over many generations; and (2) spatial coevolution produces training examples (“parasites”) that specifically target weaknesses in models (“hosts”). The precise mechanisms by which the combination of spatial embedding and coevolution produces these results are still not well understood. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning – concept learning,

• Type: Conference
• Year: 2005
• Where: GECCO
• Authors: Nathan Williams, Melanie Mitchell
• Keywords: GECCO 2005, Spatial Coevolution, Spatial Evolutionary Methods, Spatial Evolutionary Scheme