The interaction of learning rules and population turnover can drive cultural evolution

Abstract

**Author(s):** Barrett, B; Kandler, A; Aplin, L Cultural evolution is usually framed in terms of transmission biases or behavioral transformation via cognitive biases, although there is a third dimension that is often ignored: learning through reward. This process of internal selection that happens when socially learned behaviors are used by individuals, has been hypothesized to play a critical role in the evolution of adaptiveness of cultural traits, as they are either maintained or abandoned over the course of repeated production. To date, this has remained a verbal argument. To test this argument, we construct an agent based model where acquisition and production are linked, as acquisition is conditioned on association, as well as behavioral frequencies of associates. We show that variation in the learning rules that govern production influence the diffusion of a novel behavior. We further show that these effects can affect the inferential power of two popular models in the field of animal culture: Network Based Diffusion Analysis and Experience Weighted Attraction models. We then allow for dynamic networks of populations, and show how the social process of population turnover interacts with reinforcement learning to drive the cultural evolution of efficiency. Different regimes of population turnover generate optimal, neutral or sub-optimal selection for a more efficient behavior, when compared against static populations. These two studies generate new predictions for how reinforcement learning can influence cultural outcomes, and highlight un-discussed consequences for current practices in the field. The formulation of our model also encourages more rigorous definitions for social learning strategies and biases, as they might target the process of acquisition or production, or both, yet have been discussed interchangeably to date. They also provide theoretical support for the hypothesis that naive learners, introduced through population turnover, play a crucial role in resampling payoff landscapes.