TY - JOUR
T1 - Cultural diffusion dynamics depend on behavioural production rules
AU - Chimento, Michael
AU - Barrett, Brendan J.
AU - Kandler, Anne
AU - Aplin, Lucy M.
N1 - Publisher Copyright:
© 2022 The Authors.
PY - 2022/8/10
Y1 - 2022/8/10
N2 - Culture is an outcome of both the acquisition of knowledge about behaviour through social transmission, and its subsequent production by individuals. Acquisition and production are often discussed or modelled interchangeably, yet to date no study has explored the consequences of their interaction for cultural diffusions. We present a generative model that integrates the two, and ask how variation in production rules might influence diffusion dynamics. Agents make behavioural choices that change as they learn from their productions. Their repertoires may also change, and the acquisition of behaviour is conditioned on its frequency. We analyse the diffusion of a novel behaviour through social networks, yielding generalizable predictions of how individual-level behavioural production rules influence population-level diffusion dynamics. We then investigate how linking acquisition and production might affect the performance of two commonly used inferential models for social learning; network-based diffusion analysis, and experience-weighted attraction models. We find that the influence that production rules have on diffusion dynamics has consequences for how inferential methods are applied to empirical data. Our model illuminates the differences between social learning and social influence, demonstrates the overlooked role of reinforcement learning in cultural diffusions, and allows for clearer discussions about social learning strategies.
AB - Culture is an outcome of both the acquisition of knowledge about behaviour through social transmission, and its subsequent production by individuals. Acquisition and production are often discussed or modelled interchangeably, yet to date no study has explored the consequences of their interaction for cultural diffusions. We present a generative model that integrates the two, and ask how variation in production rules might influence diffusion dynamics. Agents make behavioural choices that change as they learn from their productions. Their repertoires may also change, and the acquisition of behaviour is conditioned on its frequency. We analyse the diffusion of a novel behaviour through social networks, yielding generalizable predictions of how individual-level behavioural production rules influence population-level diffusion dynamics. We then investigate how linking acquisition and production might affect the performance of two commonly used inferential models for social learning; network-based diffusion analysis, and experience-weighted attraction models. We find that the influence that production rules have on diffusion dynamics has consequences for how inferential methods are applied to empirical data. Our model illuminates the differences between social learning and social influence, demonstrates the overlooked role of reinforcement learning in cultural diffusions, and allows for clearer discussions about social learning strategies.
KW - agent-based model
KW - cultural evolution
KW - experience weighted attraction models
KW - network-based diffusion analysis
KW - reinforcement learning
KW - social learning
UR - http://www.scopus.com/inward/record.url?scp=85135731348&partnerID=8YFLogxK
U2 - 10.1098/rspb.2022.1001
DO - 10.1098/rspb.2022.1001
M3 - Article
SN - 0962-8452
VL - 289
JO - Proceedings of the Royal Society B: Biological Sciences
JF - Proceedings of the Royal Society B: Biological Sciences
IS - 1980
M1 - 20221001
ER -