RT Journal Article
SR Electronic
T1 Social learning through associative processes: A computational theory
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 446906
DO 10.1101/446906
A1 Johan Lind
A1 Stefano Ghirlanda
A1 Magnus Enquist
YR 2018
UL http://biorxiv.org/content/early/2018/10/18/446906.abstract
AB Social transmission of information is a key phenomenon in the evolution of behavior and in the establishment of traditions and culture. The diversity of social learning phenomena has engendered a diverse terminology and numerous ideas about underlying learning mechanisms, at the same time that some researchers have called for a unitary analysis of social learning in terms of associative processes. Leveraging previous attempts and a recent computational formulation of associative learning, we analyze the following learning scenarios in some generality: learning responses to social stimuli, including learning to imitate; learning responses to non-social stimuli; learning sequences of actions; learning to avoid danger. We conceptualize social learning as situations in which stimuli that arise from other individuals have an important role in learning. This role is supported by genetic predispositions that either cause responses to social stimuli or enable social stimuli to reinforce specific responses. Our explorations show that, when guided by such predispositions, associative processes can give rise to a wide variety of social learning phenomena, such as stimulus and local enhancement, contextual imitation and simple production imitation, observational conditioning, and social and response facilitation. In addition, we clarify how associative mechanisms can result in transfer of information and behavior from experienced to naïve individuals.