Modeling Higher-Order Adaptive Evolutionary Processes by Multilevel Adaptive Agent Models

Abstract

In this paper a fourth-order adaptive agent model based on a multilevel reified network model is introduced to describe different orders of adaptivity of the agent?s biological embodiment, as found in a case study on evolutionary processes. The adaptive agent model describes how the causal pathways for newly developed features affect the causal pathways of already existing features. This makes these new features one order of adaptivity higher than the existing ones. A network reification approach is shown to be an adequate means to model this.