Microscopic analysis is a standard approach in the study of robot behaviour. Typically, the approach comprises the analysis of a single (or sometimes a few) robot-environment system(s) to reveal specific properties of robot behaviour. In contrast to microscopic analysis, macroscopic analysis focuses on averaged properties of systems. The advantage is that such a property is easier to generalize so that it can be established to what extent the property is universal. This paper investigates whether a macroscopic analysis can reveal a universal property of adaptive behaviour in a robot model of foraging behaviour. Our analysis reveals that the step lengths of the most successful robots are distributed according to a Levy-flight distribution. From studies on a variety of natural species, it is known that such a distribution constitutes a universal property of foraging behaviour. Thereafter, we discuss an example of how macroscopic analysis can be applied to existing research in evolutionary robotics, and relate the macroscopic and microscopic analyses of foraging behaviour to the framework of scientific research described by Cohen (1995, Empirical Methods for Artificial Intelligence (Cambridge MA: MIT Press)). We conclude that macroscopic analysis may predict universal properties of adaptive behaviour and that it may complement microscopic analysis in the study of adaptive behaviour.