Sparse code of conflict in a primate society

Bryan C. Daniels, David C. Krakauer, Jessica C. Flack

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Animals living in groups collectively produce social structure. In this context individuals make strategic decisions about when to cooperate and compete. This requires that individuals can perceive patterns in collective dynamics, but how this pattern extraction occurs is unclear. Our goal is to identify a model that extracts meaningful social patterns from a behavioral time series while remaining cognitively parsimonious by making the fewest demands on memory. Using fine-grained conflict data from macaques, we show that sparse coding, an important principle of neural compression, is an effective method for compressing collective behavior. The sparse code is shown to be efficient, predictive, and socially meaningful. In our monkey society, the sparse code of conflict is composed of related individuals, the policers, and the alpha female. Our results suggest that sparse coding is a natural technique for pattern extraction when cognitive constraints and small sample sizes limit the complexity of inferential models. Our approach highlights the need for cognitive experiments addressing how individuals perceive collective features of social organization.

Original languageEnglish (US)
Pages (from-to)14259-14264
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume109
Issue number35
DOIs
StatePublished - Aug 28 2012

Keywords

  • Cognition
  • Collective computation
  • Social complexity
  • Social niche construction
  • Statistical inference

ASJC Scopus subject areas

  • General

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