Introduction

All too often theoretically minded scientists soar off into an abstract mathematical world that seemingly makes little contact with empirical reality. The field of animal social learning and tradition has its very own assortment of theory, although in truth it is a somewhat paltry portion, and the mathematics rarely get that sophisticated. Nonetheless, the modelers and the empirical scientists, while perhaps converging, have for the most part yet to meet in any consensus of shared goals and understanding. As the most effective mathematical models in science are undoubtedly those making clear, empirically testable predictions, it would obviously be of value if the mathematics had some utility to other researchers in the field of animal social learning. Moreover, as the best models are those with assumptions well informed by empirical findings, it would also clearly help if social learning researchers collected the kind of information that was relevant to grounding the models.

The over-arching goal of this article is to contribute towards the further integration of empirical and theoretical work in animal social learning. While this is a worthy long-term objective, it is apparent that such an integration is unlikely to happen overnight. At the time of writing, most of the mathematical theory in our field has been developed without the benefit of a thorough understanding of animal social learning, in fact, largely without nonhuman animals in mind.