Random Copying Research Articles

On randomly changing conformity bias in cultural transmission

Humans and nonhuman animals display conformist as well as anticonformist biases in cultural transmission. Whereas many previous mathematical models have incorporated constant conformity coefficients, empirical research suggests that the extent of (anti)conformity in populations can change over time. We incorporate stochastic time-varying conformity coefficients into a widely used conformity model, which assumes a fixed number n of "role models" sampled by each individual. We also allow the number of role models to vary over time ([Formula: see text]). Under anticonformity, nonconvergence can occur in deterministic and stochastic models with different parameter values. Even if strong anticonformity may occur, if conformity or random copying (i.e., neither conformity nor anticonformity) is expected, there is convergence to one of the three equilibria seen in previous deterministic models of conformity. Moreover, this result is robust to stochastic variation in [Formula: see text] However, dynamic properties of these equilibria may be different from those in deterministic models. For example, with random conformity coefficients, all equilibria can be stochastically locally stable simultaneously. Finally, we study the effect of randomly changing weak selection. Allowing the level of conformity, the number of role models, and selection to vary stochastically may produce a more realistic representation of the wide range of group-level properties that can emerge under (anti)conformist biases. This promises to make interpretation of the effect of conformity on differences between populations, for example those connected by migration, rather difficult. Future research incorporating finite population sizes and migration would contribute added realism to these models.

Cultural and evolutionary dynamics with best-of-k learning when payoffs are uncertain

Social learning not only takes the form of random copying of other individuals, but also involves learners’ choice of what to learn or from whom to learn. Best-of-k learning refers to a kind of success-biased social learning strategy in which a learner randomly samples k exemplars from the population and imitates the most ”successful” one, or the one gaining the highest payoff. While it is intuitive that best-of-k learning can promote the spread of superior variants and thereby enable cumulative cultural evolution, a previous mathematical analysis has shown that it may sometimes result in maladaptive cultural evolution when the payoffs associated with cultural variants vary stochastically. If so, best-of-k learners may be selectively disfavored and in the long run replaced by unbiased learners, who simply copy someone chosen at random. Here we develop new mathematical models that are more simplified and mathematically tractable than the previous model to achieve a fuller analysis of cultural and evolutionary dynamics involving best-of-k learning and stochastic payoffs. We find that best-of-k learning, unlike unbiased learning, can facilitate the invasion of an on average inferior variant that sometimes gives a very high payoff, destabilize a population fixed with a variant that is on average superior but occasionally results in a very low payoff, and maintain cultural polymorphism at equilibrium. Considering gene-culture coevolution of learning rules and cultural variants, under the assumption that social learning is always faithful, it is shown that a population of best-of-k learners at the culturally polymorphic state can always be invaded by unbiased learners and eventually converges to a culturally monomorphic state. Nonetheless, we show that best-of-k learning can be stable against invasion by unbiased learning if social learning is sometimes combined with individual learning.

Evolving conformity: Conditions favouring conformist social learning over random copying

There is a growing interest in the relative benefits to the learner of the different social learning strategies used to transmit information between conspecifics, and in the extent to which they require input from individual learning. To date, theoretical models have tended to examine the success of particular strategies in relation to specific parameters or circumstances. This study employs individual-based simulations to derive the optimal proportion of individual learning that co-exists with random copying and conformist social learning strategies in populations experiencing wide-ranging variation in levels of environmental change, reproductive turnover, learning error, and individual learning costs. Predictions derived from the literature – that optimal levels of individual learning will be higher for both strategies when the rate of environmental change is higher, and when reproductive turnover and individual learning costs are lower, are supported. Contrary to the theoretical prediction, optimal levels of individual learning are sometimes higher under higher levels of learning error, particularly when reproductive rates are low. Results for the two strategies are qualitatively similar, but demonstrate numerous parameter combinations under which random copying is fitter than conformist social learning. Contrary to established expectations, the strategy employing the lesser proportion of individual learning is not always the fittest.

Most Cancer Mutations Are Due to Random DNA Copying ‘Mistakes’

Most Cancer Mutations Are Due to Random DNA Copying ‘Mistakes’

The Alchian-Allen Theorem and the Economics of Internet Animals

The Alchian-Allen Theorem and the Economics of Internet Animals

Success-biased social learning: Cultural and evolutionary dynamics

Success bias is a social learning strategy whereby learners tend to acquire the cultural variants of successful individuals. I develop a general model of success-biased social learning for discrete cultural traits with stochastic payoffs, and investigate its dynamics when only two variants are present. I find that success bias inherently favors rare variants, and consequently performs worse than unbiased imitation (i.e. random copying) when success payoffs are at least mildly stochastic and the optimal variant is common. Because of this weakness, success bias fails to replace unbiased imitation in an evolutionary model when selection is fairly weak or when the environment is relatively stable, and sometimes fails to invade at all. I briefly discuss the optimal strength of success bias, the complicated nature of defining success in social learning contexts, and the value of variant frequency as an important source of information to social learners. I conclude with predictions regarding the prevalence of success bias in different behavioral domains.

NEUTRAL EVOLUTION: A NULL MODEL FOR LANGUAGE DYNAMICS

We review the task of aligning simple models for language dynamics with relevant empirical data, motivated by the fact that this is rarely attempted in practice despite an abundance of abstract models. We propose that one way to meet this challenge is through the careful construction of null models. We argue in particular that rejection of a null model must have important consequences for theories about language dynamics if modeling is truly to be worthwhile. Our main claim is that the stochastic process of neutral evolution (also known as genetic drift or random copying) is a viable null model for language dynamics. We survey empirical evidence in favor and against neutral evolution as a mechanism behind historical language changes, highlighting the theoretical implications in each case.

RANDOM COPYING IN SPACE

Random copying is a simple model for population dynamics in the absence of selection, and has been applied to both biological and cultural evolution. In this work, we investigate the effect that spatial structure has on the dynamics. We focus in particular on how a measure of the diversity in the population changes over time. We show that even when the vast majority of a population's history may be well-described by a spatially-unstructured model, spatial structure may nevertheless affect the expected level of diversity seen at a local scale. We demonstrate this phenomenon explicitly by examining the random copying process on small-world networks, and use our results to comment on the use of simple random-copying models in an empirical context.

An experimental comparison of human social learning strategies: payoff-biased social learning is adaptive but underused

Analytical models have identified a set of social learning strategies that are predicted to be adaptive relative to individual (asocial) learning. In the present study, human participants engaged in an ecologically valid artifact-design task with the opportunity to engage in a range of social learning strategies: payoff bias, conformity, averaging and random copying. The artifact (an arrowhead) was composed of multiple continuous and discrete attributes which jointly generated a complex multimodal adaptive landscape that likely reflects actual cultural fitness environments. Participants exhibited a mix of individual learning and payoff-biased social learning, with negligible frequencies of the other social learning strategies. This preference for payoff-biased social learning was evident from the initial trials, suggesting that participants came into the study with an intrinsic preference for this strategy. There was also a small but significant increase in the frequency of payoff-biased social learning over sessions, suggesting that strategy choice may itself be subject to learning. Frequency of payoff-biased social learning predicted both absolute and relative success in the task, especially in a multimodal (rather than unimodal) fitness environment. This effect was driven by a minority of hardcore social learners who copied the best group member on more than half of trials. These hardcore social learners were also above-average individual learners, suggesting a link between individual and social learning ability. The lower-than-expected frequency of social learning may reflect the existence of information producer–scrounger dynamics in human populations.

Ceramic diversity, random copying, and tests for selectivity in ceramic production

This paper examines the evidence for selective reproduction of ceramic types based on their evolving frequency distribution, and on correlations of the abundance of types with underlying functional characteristics. How can we tell if a variant has been preferentially selected or discriminated against, and become more or less frequent than would be expected under pure drift (i.e. random copying, with the compounding over time of proportionate sampling error)? We examined a database of Hittite ceramic bowl types from two successive Phases of occupation of the Upper City of Boğazköy–Hattusa, capital of the Hittite empire and the largest Bronze Age settlement in Turkey. We applied two tests used in genetics to assess departures from neutrality, to assess selectivity in rates of reproduction of ceramic bowl types (the Ewens-Watterson and Slatkin's Exact tests). We also examined the effects of ceramic fabric and vessel dimensions on changes in vessel abundance between the two Phases, using regression analysis. We found that while the frequency distribution of rim sherds did not in itself enable us to reject the null hypothesis of random copying, closer examination of the characteristics of these types enabled us to recognize latent dimensions of functional variability (including ware type and bowl diameter) that had demonstrably been the subject of selective decision-making by the potters. The present case study suggests that we should be wary of applying the neutral model from genetics uncritically in archaeology, because it is much harder to prove that the cultural traits whose frequencies are being modelled are genuinely functionally equivalent (as that model requires).

Paddy and Biddy no more: An evolutionary analysis of the decline in Irish Catholic forenames among descendants of 19th century Irish migrants to Britain

Background: Recent research into cultural evolution has suggested that the distribution of many culturally neutral traits, including forenames, can be explained by a model of random copying, analogous to the process of random genetic drift.Aim: We test the proposition that in particular circumstances some forenames may not be neutral but, again by analogy with population genetics, may be subject to selection.Data sources and methods: The case study used to test this idea is the situation of Irish migrants and their descendants in late 19th century England and Wales. We compare forename frequencies among first- and second-generation Irish at the 1881 census of England and Wales, and show that in all counties studied the frequencies of the indicative Irish Catholic forenames Patrick and Bridget were much lower in the second-generation Irish, a result which applies consistently throughout 17 counties of England and Wales chosen for their substantial Irish-born populations.Conclusion: These results are explicable under a model of cultural evolution, informed by the historiography of Irish migration after the Great Famine, including the perception of derogatory Irish stereotypes exemplified by the sobriquets ‘Paddy’ and ‘Biddy’.

The Cultural Transmission of Great Basin Projectile-Point Technology II: An Agent-Based Computer Simulation

We present an agent-based computer simulation that extends a previous experimental simulation (Mesoudi and O"Brien 2008) of the cultural transmission of projectile-point technology in the prehistoric Great Basin, with participants replaced with computer-generated agents. As in the experiment, individual learning is found to generate low correlations between artifact attributes, whereas indirectly biased cultural transmission (copying the point design of the most successful hunter) generates high correlations between artifact attributes. These results support the hypothesis that low attribute correlations in prehistoric California resulted from individual learning, and high attribute correlations in prehistoric Nevada resulted from indirectly biased cultural transmission. However, alternative modes of cultural transmission, including conformist transmission and random copying, generated similarly high attribute correlations as indirect bias, suggesting that it may be difficult to infer which transmission rule generated this archaeological pattern. On the other hand, indirect bias out-performed all other cultural-transmission rules, lending plausibility to the original hypothesis. Importantly, this advantage depends on the assumption of a multimodal adaptive landscape in which there are multiple locally optimal artifact designs. Indeed, in unimodal fitness environments no cultural transmission rule outperformed individual learning, highlighting how the shape of the adaptive landscape within which cultural evolution occurs can strongly influence the dynamics of cultural transmission. Generally, experimental and computer simulations can be useful in answering questions that are difficult to address with archaeological data, such as identifying the consequences of different modes of cultural transmission or exploring the effect of different selective environments.

Random copying, frequency-dependent copying and culture change

Previous evolutionary analyses of human culture have found that a simple model of random copying, analogous to neutral genetic drift, can generate the distinct power-law frequency distribution of cultural traits that is typical of various real-world cultural datasets, such as first names, patent citations and prehistoric pottery types. Here, we use agent-based simulations to explore the effects of frequency-dependent copying (e.g., conformity and anti-conformity) on this power-law distribution. We find that when traits are actively selected on the basis of their frequency, then the power-law distribution is severely disrupted. Conformity generates a “winner-takes-all” distribution in which popular traits dominate, while anti-conformity generates a “humped” distribution in which traits of intermediate frequency are favoured. However, a more passive frequency-dependent “trimming”, in which traits are selectively ignored on the basis of their frequency, generates reasonable approximations to the power-law distribution. This frequency-dependent trimming may therefore be difficult to distinguish from genuine random copying using population-level data alone. Implications for the study of both human and nonhuman culture are discussed.

Regular rates of popular culture change reflect random copying

Almost by definition, “popular culture” reflects the effects of most people imitating those around them. At the same time, trends and fashions are constantly changing, with future outcomes potentially irrational and nearly impossible to predict. A simple null model, which captures these seemingly conflicting tendencies of conformity and change, involves the random copying of cultural variants between individuals, with occasional innovation. Here, we show that the random-copying model predicts a continual flux of initially obscure new ideas (analogous to mutations) becoming highly popular by chance alone, such that the turnover rate on a list of most popular variants depends on the list size and the amount of innovation but not on population size. We also present evidence for remarkably regular turnover on “pop charts”—including the most popular music, first names, and dog breeds in 20th-century United States—which fits this expectation. By predicting parametric effects on the turnover of popular fashion, the random-copying model provides an additional means of characterizing collective copying behavior in culture evolution.

Drift as a mechanism for cultural change: an example from baby names.

In the social sciences, there is currently no consensus on the mechanism by which cultural elements come and go in human society. For elements that are value-neutral, an appropriate null model may be one of random copying between individuals in the population. We show that the frequency distributions of baby names used in the United States in each decade of the twentieth century, for both males and females, obey a power law that is maintained over 100 years even though the population is growing, names are being introduced and lost every decade and large changes in the frequencies of specific names are common. We show that these distributions are satisfactorily explained by a simple process in which individuals randomly copy names from each other, a process that is analogous to the infinite-allele model of population genetics with random genetic drift. By its simplicity, this model provides a powerful null hypothesis for cultural change. It further explains why a few elements inevitably become highly popular, even if they have no intrinsic superiority over alternatives. Random copying could potentially explain power law distributions in other cultural realms, including the links on the World Wide Web.

Practice Makes Within 5% of Perfect: Visual Perception, Motor Skills, and Memory in Artifact Variation

Practice Makes Within 5% of Perfect: Visual Perception, Motor Skills, and Memory in Artifact Variation