Experimental and theoretical models of human cultural evolution

Kempe, Marius; Mesoudi, Alex

doi:10.1002/wcs.1288

Cited by 21 publications

(20 citation statements)

References 85 publications

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“…Overall, our study shows that, depending on the chosen measure of performance, the impact of social learning can change dramatically. Social learning has different effects, depending on whether one is interested in the collective performance (e.g., the group comes up with a unique collective solution (Kempe and Mesoudi, 2014) or develops a new cultural innovation (Derex and Boyd, 2016;Derex and Boyd, 2015)), or in the average individual performance (see, e.g., (Lazer and Friedman, 2007;Mason and Watts, 2012;Barkoczi and Galesic, 2016)). Here, it is interesting to point out that the measures of performance are not limited to the two instances that we have studied in this work.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, one inconsistent aspect in extant research concerns the measurement of performance: whereas some studies rely on the average payoff of the group members (Mason, Jones, et al, 2008;Lazer and Friedman, 2007;Barkoczi and Galesic, 2016), others focus on the best solution found by the group (Cooper et al, 2010;Kempe and Mesoudi, 2014;Derex, Perreault, et al, 2018). In fact, these two measurements assess different aspects of the group dynamics: the average performance indicates how much group members can individually benefit from social learning, while the best solution is an indicator of the group's collective performance.…”

Section: Introductionmentioning

confidence: 99%

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The social dynamics of collective problem-solving

Yahosseini

Moussaïd

2019

Preprint

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When searching for solutions to a problem, people often rely on the observation of their peers. How does this process of social learning impact the individual and the group's performance? On the one hand, research has shown that individuals benefit from social learning in numerous situations and across many domains. Through social learning, individuals can access good solutions found by others, improve them, and share them in turn. On the other hand, this individual benefit may come at a cost: An excessive tendency to copy others often decreases the overall exploration volume of the group, thus reducing the diversity of discovered solutions, and eventually impairing the collective performance.Here we investigate the conditions under which social learning can be beneficial or detrimental to individuals and to the group. For that, we model problem-solving as a search task and simulate various amounts of social learning. We avoid model specific considerations by relying on a simple framework whereby individuals gradually explore the search environment -a two-dimensional landscape of solutions -while being attracted to the best solution of the group. Our results highlight a collective search dilemma: When group members learn from one another, they tend to improve their own individual performance at the expense of the collective performance. How is this dilemma affected by the structure of the search environment? By varying two structural aspects of the search environment, our results reveal that the negative effect of the dilemma is mitigated in more difficult environments. Finally, we show that single individuals can profit from a high propensity of social learning, which in turn is damaging for the other group members. As a consequence, if individuals continually adapt their behavior to maximize their own payoff, groups converge to a sub-optimal level of social learning. Unraveling these intricate social dynamics helps to understand the complex picture of collective problem-solving.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The social dynamics of collective problem-solving

Yahosseini

Moussaïd

2019

Preprint

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“…Wisdom of crowds methods are easily scalable as they allow for arbitrarily large group sizes and can yield to accurate solutions (Mannes et al, 2014;Herzog et al, 2019;Surowiecki, 2004). One drawback, however, is that most statistical aggregation techniques cannot be easily applied to complex, multi-dimensional solutions, such as when optimizing a protein folding configuration (Cooper et al, 2010;Romero et al, 2013), improving quantum transport techniques (Sørensen et al, 2016), or trying to solve a jigsaw puzzle (Kempe and Mesoudi, 2014). Thus for problems that have a complex solution structure, the most common practice consists in collecting a large number of independent and hence diverse solutions and choosing the best one at the end (Cooper et al, 2010;Sørensen et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Transmission Chains or Independent Solvers? A Comparative Study of Two Collective Problem-Solving Methods

Yahosseini

Moussaïd

2019

Preprint

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AbstractGroups can be very successful problem-solvers. This collective achievement crucially depends on how the group is structured, that is, how information flows between members and how individual contributions are merged. Numerous methods have been proposed, which can be divided into two major categories: those that involve an exchange of information between the group members, and those that do not. Here we compare two instances of such methods for solving complex problems: (1) transmission chains, where individuals tackle the problem one after the other, each one building on the solution of the predecessor and (2) groups of independent solvers, where individuals tackle the problem independently, and the best solution found in the group is selected afterwards.By means of numerical simulations and experimental observations, we show that the best performing method is determined by the interplay between two key factors: the skills of the individuals and the difficulty of the problem. We find that transmission chains are superior either when the problem is rather easy, or when the group is composed of rather unskilled individuals. On the contrary, groups of independent solvers are preferable for harder problems or for groups of rather skillful individuals. Finally, we deepen the comparison by studying the impact of the group size and diversity. Our research stresses that efficient collective problem-solving requires a good matching between the nature of the problem and the structure of the group.

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“…One strategy used a confederate model, similar to experiment 2 in Higgins et al (1989). The second strategy used a participant replacement procedure (Caldwell & Millen, 2008a, 2008bKempe & Mesoudi, 2014;Mesoudi & Whiten, 2008;Baum et al, 2004), in which one new participant could learn about the behavior of a previous participant before working on an experimental task. If our hypothesis is correct, then superstitious behavior and the illusion of control will be more likely for participants in a replacement procedure compared with participants who are individually exposed to the same task.…”

Section: Introductionmentioning

confidence: 99%

Behavior and illusions: a model to study superstition in a participant replacement experiment

Benvenuti

Toledo

Velasco

et al. 2018

Psicol. Refl. Crít.

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The notion of superstitious behavior can provide a basic background for understanding such notions as illusions and beliefs. The present study investigated the social mechanism of the transmission of superstitious behavior in an experiment that utilized participant replacement. The sample was composed of a total of 38 participants. Participants performed a task on a computer: they could click a colored rectangle using the mouse. When the rectangle was in a particular color, the participants received points independently of their behavior (variable time schedule). When the color of the rectangle was changed, no points were presented (extinction). Under an Individual Exposure condition, ten participants worked alone on the task. Other participants were exposed to the same experimental task under a Social Exposure condition, in which each participant first learned by observation and then worked on the task in a participant replacement (chain) procedure. The first participant in each chain in the Social Exposure condition was a confederate who worked on the task "superstitiously," clicking the rectangle when points were presented. Superstitious responding was transmitted because of the behavior of the confederate. This also influenced estimates of personal control. These findings suggest that social learning can facilitate the acquisition and maintenance of superstitious behavior and the illusion of control. Our data also suggest that superstitious behavior and the illusion of control may involve similar learning principles.

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Experimental and theoretical models of human cultural evolution

Cited by 21 publications

References 85 publications

The social dynamics of collective problem-solving

The social dynamics of collective problem-solving

Transmission Chains or Independent Solvers? A Comparative Study of Two Collective Problem-Solving Methods

Behavior and illusions: a model to study superstition in a participant replacement experiment

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