A neural network model for the evolution of reconstructive social learning.

ABSTRACT: Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transmitted information must be reconstructed by the learner, based on the learner's previous knowledge and cognition. To represent the reconstructive nature of social learning, we present a modelling framework that incorporates the evolution of a neural network and a simple yet biologically realistic learning mechanism. The framework encompasses various forms of individual and social learning and allows the investigation of their interplay. Individual-based simulations reveal that an effective neural network structure rapidly evolves, leading to ada

SUBMITTER: Chisausky J 

PROVIDER: S-EPMC12041464 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature