Everybody herds, sometimes: cumulative advantage as a product of rational learning

Abstract

We propose a model of cumulative advantage (CA) as an unintended consequence of the choices of a population of individuals. Each individual searches for a high quality object from a set comprising high and low quality objects. Individuals rationally learn from their own experience with objects (reinforcement learning) and from the observation of others’ choices (social learning). We show that CA emerges inexorably as individuals rely more on social learning and as they learn from more rather than fewer others. Our theory argues that CA has social dilemma features: the benefits of CA could be enjoyed with modest drawbacks provided individuals would practice restraint in their social learning. However, when practiced by everyone such restraint goes against the individual’s self-interest.