Robust Evolutionary Algorithm Design for Socio-Economic Simulation : A Correction

Abstract

Recently we have discovered an error in the implementation of the mutation operator in our earlier work on robust evolutionary algorithm design for socio-economic simulation. The original paper compared two commonly used approaches to socio-economic simulation. In the first approach parameter settings for the evolutionary algorithm are directly derived from the underlying economic model while in the second approach to social learning parameter settings are chosen so as to optimise evolutionary algorithm performance. Main conclusions of the original paper are that the first approach may hinder the performance of the evolutionary algorithm and thereby hinder agent learning, that is, that social learning evolutionary algorithms are able to overcome the so-called spite-effect and obtain high profit outcomes. These main conclusions are still confirmed when the error in the mutation operator is corrected. However, the convergence behaviour of some of the individual runs differs significantly from the (incorrect) results presented in the earlier papers.