A Bayesian approach to the evolution of social learning

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

There has been much interest in understanding the evolution of social learning. Investigators have tried to understand when natural selection will favor individuals who imitate others, how imitators should deal with the fact that available models may exhibit different behaviors, and how social and individual learning should interact. In all of this work, social learning and individual learning have been treated as alternative, conceptually distinct processes. Here we present a Bayesian model in which both individual and social learning arise from a single inferential process. Individuals use Bayesian inference to combine social and nonsocial cues about the current state of the environment. This model indicates that natural selection favors individuals who place heavy weight on social cues when the environment changes slowly or when its state cannot be well predicted using nonsocial cues. It also indicates that a conformist bias should be a universal aspect of social learning.

Original languageEnglish (US)
Pages (from-to)449-459
Number of pages11
JournalEvolution and Human Behavior
Volume33
Issue number5
DOIs
StatePublished - Sep 2012
Externally publishedYes

Fingerprint

Bayes Theorem
learning
Cues
Genetic Selection
Learning
natural selection
social work
Research Personnel
Weights and Measures
Social Learning
Natural Selection

Keywords

  • Bayesian learning
  • Bet-hedging
  • Conformism
  • Cultural evolution
  • Learning psychology
  • Origin of culture

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

Cite this

A Bayesian approach to the evolution of social learning. / Perreault, Charles; Moya, Cristina; Boyd, Robert.

In: Evolution and Human Behavior, Vol. 33, No. 5, 09.2012, p. 449-459.

Research output: Contribution to journalArticle

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