scholarly journals Population Size and Cumulative Cultural Evolution: Fewer Heads Can Be Better than Many

2018 ◽  
Author(s):  
Nicolas Fay ◽  
Naomi De Kleine ◽  
Bradley Walker ◽  
Christine Anna Caldwell
Keyword(s):  
Social Learning ◽  
Population Size ◽  
Cultural Evolution ◽  
Large Scale ◽  
Individual Learning ◽  
Flight Distance ◽  
Learning Condition ◽  
Scale Experiment ◽  
Cumulative Cultural Evolution ◽  
The Individual

The extent to which larger populations enhance cumulative cultural evolution (CCE) is contentious. We report a large-scale experiment (N=543) that investigates the CCE of technology (paper planes and their flight distances) using a transmission chain design. Population size was manipulated such that participants could learn from the paper planes constructed by 1, 2 or 4 models from the prior generation. These social learning conditions were compared to an asocial Individual Learning condition in which individual participants made repeated attempts at constructing a paper plane, without having access to any planes produced by other participants. Larger populations generated greater variation in plane performance and gave participants access to better-adapted planes, but this did not enhance CCE. In fact, there was an inverse relationship between population size and CCE: plane flight distance did not improve over the experimental generations in the 2-Model and 4-Model conditions, but did improve over generations in the 1-Model social learning condition. The incremental improvement in plane flight distance in the 1-Model social learning condition was comparable to that in the Individual Learning condition, highlighting the importance of trial-and-error learning to artefact innovation and adaptation. In the context of this experiment, we conclude that larger populations do not enhance artefact performance via CCE, and that it may be only under certain specific conditions that larger population sizes enhance CCE.

scholarly journals Increasing population size can inhibit cumulative cultural evolution

2019 ◽  
Vol 116 (14) ◽  
pp. 6726-6731 ◽  
Author(s):  
Nicolas Fay ◽  
Naomi De Kleine ◽  
Bradley Walker ◽  
Christine A. Caldwell
Keyword(s):  
Social Learning ◽  
Population Size ◽  
Cultural Evolution ◽  
Large Scale ◽  
Individual Learning ◽  
Flight Distance ◽  
Learning Condition ◽  
Scale Experiment ◽  
Cumulative Cultural Evolution ◽  
The Individual

The extent to which larger populations enhance cumulative cultural evolution (CCE) is contentious. We report a large-scale experiment (n= 543) that investigates the CCE of technology (paper planes and their flight distances) using a transmission-chain design. Population size was manipulated such that participants could learn from the paper planes constructed by one, two, or four models from the prior generation. These social-learning conditions were compared with an asocial individual-learning condition in which individual participants made repeated attempts at constructing a paper plane, without having access to any planes produced by other participants. Larger populations generated greater variation in plane performance and gave participants access to better-adapted planes, but this did not enhance CCE. In fact, there was an inverse relationship between population size and CCE: plane flight distance did not improve over the experimental generations in the 2-Model and 4-Model conditions, but did improve over generations in the 1-Model social-learning condition. The incremental improvement in plane flight distance in the 1-Model social-learning condition was comparable to that in the Individual Learning condition, highlighting the importance of trial-and-error learning to artifact innovation and adaptation. An exploratory analysis indicated that the greater variation participants had access to in the larger populations may have overwhelmed their working memory and weakened their ability to selectively copy the best-adapted plane(s). We conclude that larger populations do not enhance artifact performance via CCE, and that it may be only under certain specific conditions that larger population sizes enhance CCE.

scholarly journals The evolution of high-fidelity social learning

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200090
Author(s):  
Marcel Montrey ◽  
Thomas R. Shultz
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
Bayesian Model ◽  
Individual Learning ◽  
High Fidelity ◽  
Human Culture ◽  
Cumulative Cultural Evolution ◽  
Over Time

A defining feature of human culture is that knowledge and technology continually improve over time. Such cumulative cultural evolution (CCE) probably depends far more heavily on how reliably information is preserved than on how efficiently it is refined. Therefore, one possible reason that CCE appears diminished or absent in other species is that it requires accurate but specialized forms of social learning at which humans are uniquely adept. Here, we develop a Bayesian model to contrast the evolution of high-fidelity social learning, which supports CCE, against low-fidelity social learning, which does not. We find that high-fidelity transmission evolves when (1) social and (2) individual learning are inexpensive, (3) traits are complex, (4) individual learning is abundant, (5) adaptive problems are difficult and (6) behaviour is flexible. Low-fidelity transmission differs in many respects. It not only evolves when (2) individual learning is costly and (4) infrequent but also proves more robust when (3) traits are simple and (5) adaptive problems are easy. If conditions favouring the evolution of high-fidelity transmission are stricter (3 and 5) or harder to meet (2 and 4), this could explain why social learning is common, but CCE is rare.

scholarly journals Applying the Cultural Ratchet to a Social Artefact: The Cumulative Cultural Evolution of a Language Game

2018 ◽  
Author(s):  
Nicolas Fay ◽  
T. Mark Ellison ◽  
Kristian Tylén ◽  
Riccardo Fusaroli ◽  
Bradley Walker ◽  
...  
Keyword(s):  
Cultural Evolution ◽  
Large Scale ◽  
Language Game ◽  
Communication Process ◽  
Observation Condition ◽  
Social Coordination ◽  
The Social ◽  
Scale Experiment ◽  
Human Participants ◽  
Cumulative Cultural Evolution

Material artefacts evolve by cumulative cultural evolution (CCE), the accumulation of adaptive modifications over time. We present a large-scale experiment investigating the CCE of a social artefact in transmission chains, each containing 8 adult human participants (N=408). The social artefact is what Wittgenstein calls a ‘language game’, the subset of language used to perform a particular activity; in the present study the language game is to communicate a route on a map. Two social learning conditions were compared: Observational Learning and Social Coordinative Learning. Participants tried to accurately communicate a route on a map to the next person in their transmission chain. Over the experimental generations the routes were reproduced with progressively higher accuracy in both conditions, demonstrating the CCE of the language game. The rate of CCE was comparable across conditions, but route reproduction accuracy was consistently higher in the Social Coordination condition compared to the Observation condition. In both conditions performance improved due to the accumulation of adaptive patterns of verbal route descriptions, and the progressive elimination of non-adaptive patterns. Whereas change in the content of the language game was similar across conditions, change to the communication process differed between the Observation and Social Coordination conditions. In conclusion, like material artefacts, social artefacts, in our case the language game, evolve by cumulative cultural evolution.

Copy the In-group: Group Membership Trumps Perceived Reliability, Warmth, and Competence in a Social-Learning Task

2021 ◽  
pp. 095679762110322
Author(s):  
Marcel Montrey ◽  
Thomas R. Shultz
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
Learning Strategy ◽  
Group Membership ◽  
Social Groups ◽  
Learning Task ◽  
Minimal Group Paradigm ◽  
Learning Game ◽  
Group Members ◽  
Cumulative Cultural Evolution

Surprisingly little is known about how social groups influence social learning. Although several studies have shown that people prefer to copy in-group members, these studies have failed to resolve whether group membership genuinely affects who is copied or whether group membership merely correlates with other known factors, such as similarity and familiarity. Using the minimal-group paradigm, we disentangled these effects in an online social-learning game. In a sample of 540 adults, we found a robust in-group-copying bias that (a) was bolstered by a preference for observing in-group members; (b) overrode perceived reliability, warmth, and competence; (c) grew stronger when social information was scarce; and (d) even caused cultural divergence between intermixed groups. These results suggest that people genuinely employ a copy-the-in-group social-learning strategy, which could help explain how inefficient behaviors spread through social learning and how humans maintain the cultural diversity needed for cumulative cultural evolution.

scholarly journals Migration, acculturation, and the maintenance of between-group cultural variation

2017 ◽  
Author(s):  
Alex Mesoudi
Keyword(s):  
Social Learning ◽  
Cultural Values ◽  
Cultural Evolution ◽  
Population Level ◽  
Empirical Literature ◽  
Cultural Variation ◽  
Individual Level ◽  
And Migration ◽  
The Individual ◽  
Social Learning Processes

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.

scholarly journals The effect of dispersal on rates of cumulative cultural evolution

2018 ◽  
Vol 14 (2) ◽  
pp. 20180069 ◽  
Author(s):  
M. Dyble
Keyword(s):  
Computational Model ◽  
Population Size ◽  
Cultural Evolution ◽  
Cultural Models ◽  
Independent Effect ◽  
Cultural Adaptations ◽  
Local Environments ◽  
Males And Females ◽  
Cumulative Cultural Evolution

The ability to develop cultural adaptations to local environments is critical to the biological success of humans. Although overall population size and connectedness are thought to play an important role in increasing the rate of cumulative cultural evolution, the independent effect of dispersal rules on rates of cultural evolution has not been examined. Here, a computational model is used to explore the effect of dispersal on the rate of cultural evolution in traits transmitted patrilineally (from father to son), matrilineally (mother to daughter) and bilineally (through both sexes). Two dispersal conditions are modelled: patrilocality (where females disperse and males stay) and bilocality (where either sex may disperse). The results suggest that when only females disperse, the capacity for cumulative cultural evolution in traits shared only among males is severely constrained. This occurs even though overall rates of dispersal and the number of cultural models available to males and females are identical in both dispersal conditions. The constraints on the evolution of patrilineally inherited traits could be considered to represent a process of ‘cultural inbreeding', analogous to genetic inbreeding.

scholarly journals The evolution of social learning as phenotypic cue integration

2021 ◽  
Vol 376 (1828) ◽  
Author(s):  
Bram Kuijper ◽  
Olof Leimar ◽  
Peter Hammerstein ◽  
John M. McNamara ◽  
Sasha R. X. Dall
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
Individual Learning ◽  
Cue Integration ◽  
Bet Hedging ◽  
Epigenetic Factors ◽  
Multiple Forms ◽  
Theme Issue ◽  
Fluctuating Environments ◽  
Selective Environment

Most analyses of the origins of cultural evolution focus on when and where social learning prevails over individual learning, overlooking the fact that there are other developmental inputs that influence phenotypic fit to the selective environment. This raises the question of how the presence of other cue ‘channels’ affects the scope for social learning. Here, we present a model that considers the simultaneous evolution of (i) multiple forms of social learning (involving vertical or horizontal learning based on either prestige or conformity biases) within the broader context of other evolving inputs on phenotype determination, including (ii) heritable epigenetic factors, (iii) individual learning, (iv) environmental and cascading maternal effects, (v) conservative bet-hedging, and (vi) genetic cues. In fluctuating environments that are autocorrelated (and hence predictable), we find that social learning from members of the same generation (horizontal social learning) explains the large majority of phenotypic variation, whereas other cues are much less important. Moreover, social learning based on prestige biases typically prevails in positively autocorrelated environments, whereas conformity biases prevail in negatively autocorrelated environments. Only when environments are unpredictable or horizontal social learning is characterized by an intrinsically low information content, other cues such as conservative bet-hedging or vertical prestige biases prevail. This article is part of the theme issue ‘Foundations of cultural evolution’.

scholarly journals Social learning in swarm robotics

2021 ◽  
Vol 377 (1843) ◽  
Author(s):  
Nicolas Bredeche ◽  
Nicolas Fontbonne
Keyword(s):  
Social Learning ◽  
Cultural Evolution ◽  
Swarm Robotics ◽  
Collective Knowledge ◽  
Cumulative Culture ◽  
Natural Systems ◽  
Robot Swarms ◽  
Cumulative Cultural Evolution ◽  
Robotic Tasks ◽  
Behavioural Strategies

In this paper, we present an implementation of social learning for swarm robotics. We consider social learning as a distributed online reinforcement learning method applied to a collective of robots where sensing, acting and coordination are performed on a local basis. While some issues are specific to artificial systems, such as the general objective of learning efficient (and ideally, optimal) behavioural strategies to fulfill a task defined by a supervisor, some other issues are shared with social learning in natural systems. We discuss some of these issues, paving the way towards cumulative cultural evolution in robot swarms, which could enable complex social organization necessary to achieve challenging robotic tasks. This article is part of a discussion meeting issue ‘The emergence of collective knowledge and cumulative culture in animals, humans and machines’.

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