Strong conformity requires a greater proportion of asocial learning and achieves lower fitness than a payoff-based equivalent



Grove, Matt ORCID: 0000-0002-2293-8732
(2018) Strong conformity requires a greater proportion of asocial learning and achieves lower fitness than a payoff-based equivalent. ADAPTIVE BEHAVIOR, 26 (6). pp. 323-333.

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Abstract

<jats:p> There is a growing interest in the relative benefits of the different social learning strategies used to transmit information between conspecifics and in the extent to which they require input from asocial learning. Two strategies in particular, conformist and payoff-based social learning, have been subject to considerable theoretical analysis, yet previous models have tended to examine their efficacy in relation to specific parameters or circumstances. This study employs individual-based simulations to derive the optimal proportion of individual learning that coexists with conformist and payoff-based strategies in populations experiencing wide-ranging variation in levels of environmental change, reproductive turnover, learning error and individual learning costs. Results demonstrate that conformity coexists with a greater proportion of asocial learning under all parameter combinations, and that payoff-based social learning is more adaptive in 97.43% of such combinations. These results are discussed in relation to the conjecture that the most successful social learning strategy will be the one that can persist with the lowest frequency of asocial learning, and the possibility that punishment of non-conformists may be required for conformity to confer adaptive benefits over payoff-based strategies in temporally heterogeneous environments. </jats:p>

Item Type: Article
Uncontrolled Keywords: Social learning, asocial learning, reproductive rate, environmental change
Depositing User: Symplectic Admin
Date Deposited: 27 Sep 2018 15:28
Last Modified: 04 Mar 2023 17:23
DOI: 10.1177/1059712318807127
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3026824