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  3. Social Learning Through Associative Processes: A Computational Theory.
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Social learning through associative processes: a computational theory.

Johan Lind1, Stefano Ghirlanda2, Magnus Enquist3

  • 1Centre for the Study of Cultural Evolution and Department of Zoology, Stockholm University, Stockholm, Sweden.

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|April 30, 2019

View abstract on PubMed

Summary
This summary is machine-generated.

Associative processes, guided by genetic predispositions, can explain diverse social learning phenomena, including imitation and information transfer between individuals. This research offers a unified framework for understanding social learning mechanisms.

Keywords:
animal behaviouranimal cognitionanimal cultureassociative learningsocial learning

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Area of Science:

  • Behavioral Ecology
  • Cognitive Science
  • Evolutionary Psychology

Background:

  • Social transmission of information is crucial for behavior evolution, traditions, and culture.
  • Diverse terminology and proposed mechanisms exist for social learning.
  • A call for a unitary analysis of social learning via associative processes has emerged.

Purpose of the Study:

  • To analyze various social learning scenarios using a computational formulation of associative learning.
  • To conceptualize social learning as situations where social stimuli play a key role.
  • To demonstrate how associative mechanisms can explain complex social learning behaviors.

Main Methods:

  • Analysis of learning scenarios including responses to social/non-social stimuli, action sequences, and danger avoidance.
  • Conceptualization of social learning involving genetic predispositions influencing responses to social stimuli.
  • Simulations using a novel, publicly available learning simulator program.

    • Main Results:

    • Associative processes, guided by genetic predispositions, can generate diverse social learning phenomena.
    • Observed phenomena include stimulus/local enhancement, imitation (contextual and production), observational conditioning, and social/response facilitation.
    • Clarification of how associative mechanisms facilitate information and behavior transfer from experienced to naive individuals.

    Conclusions:

    • A unified associative framework can explain a wide range of social learning phenomena.
    • Genetic predispositions are key in enabling associative processes to drive social learning.
    • The developed simulator can guide future theoretical and empirical research in learning and behavior.