A rational framework for group-based selective social learning

Max Taylor-Davies*, Neil Bramley, Christopher G. Lucas

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Social learning can be a powerful tool, allowing us to acquire knowledge and adaptive behaviours while bypassing many of the costs of learning through direct experience. However, not everyone's behaviour is equally valuable to learn from, as other people's goals or preferences may differ dramatically from our own. In this paper, we consider the problem of selectively learning from others on the basis of direct and indirect inferences about their task-relevant preferences. Specifically, we focus on the setting where a social learner must generalise preference judgements across individuals using shared features and other cues, and so develop a formal account that can reconcile a seemingly disparate empirical picture of group-based selective social learning. Across three behavioural experiments, we demonstrate that people are sensitive to the contextual significance of group identity cues when choosing who to learn from in partially observed environments. We show that this behaviour cannot be accounted for by a range of simpler heuristic strategies.
Original languageEnglish
Pages (from-to)677–708
Number of pages32
JournalOpen Mind
Volume9
Early online date9 May 2025
DOIs
Publication statusPublished - 2025

Keywords / Materials (for Non-textual outputs)

  • social learning
  • social learning strategies
  • preference inference
  • theory of mind
  • rational analysis
  • Bayesian models

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