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Social Learning in Complex Networks: The Role of Building Blocks and Environmental Change

Social Learning in Complex Networks: The Role of Building Blocks and Environmental Change Daniel Barkoczi (barkoczi@mpib-berlin.mpg.de) Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany Mirta Galesic (galesic@mpib-berlin.mpg.de) Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany Abstract We explore the interaction between information sampling and the structure of the social environment in the case of two prominent social learning strategies: imitate-the-best and imitate-the-majority. In a series of simulations a group of agents made repeated choices between options. We varied the building blocks of the strategies used by agents, the structure of the social network and characteristics of the task environment. A key factor influencing strategies’ success is the speed with which they are able to respond to environmental change. In general, imitate-the-best provides a faster response compared to imitate-the-majority and larger samples help the former but hurt the latter. Less efficient networks decrease the performance of both, but are more detrimental for imitate-the-majority. Our findings highlight the role of sampling and social structure in the study of social learning, an area not sufficiently explored before. Keywords: Social learning; information sampling; social networks; simple heuristics; simulation; decision-making Introduction Humans and other animals obtain information via social learning. This is an efficient way to save the time and effort involved in individual trial-and-error learning and is known to underlie our capacity for culture. Despite the diverse list of empirical evidence for its use in the wild (Laland, 2004; McElreath, et al. 2008), theoretical models exploring the adaptive nature of social learning strategies lack sufficient detail to explain when we should expect to observe them. Most models study unstructured groups and focus only on the decision phase of implementing a strategy (e.g. imitate- the-majority), leaving open an important dimension affecting strategy performance: the interaction between information sampling and the structure of the social environment. The present study is an attempt towards filling this gap in the literature. Social learning is often based on limited samples of the social environment. Most communities consist of sizable groups where an individual cannot survey all other group members within reasonable time before making a decision. Consider migrating animals deciding between multiple directions, individuals in an organization trying to jointly solve a problem or stock traders trying to predict the best investment option (Couzin, Krause, Franks & Levin, 2005; March, 1991). In such situations the way information about options is sampled from the social environment is likely to be an important aspect of any strategy. The structure of the social network in which social learning takes place can then in turn affect the options available for sampling. Previous work has shown that different network structures and their efficiency can affect the diversity of options in the population and the time it takes groups to converge on a solution (Lazer & Friedman, 2007; Mason & Watts, 2012). How does the performance of different strategies depend on the way they sample information and on the social environment in which they are embedded? To address this question we study two representative social learning strategies: imitate-the-best and imitate-the- majority (Boyd & Richerson, 1985; Laland, 2004) and model them as decision heuristics that consist of different building blocks: search, stop and decision rules (Gigerenzer, Todd & the ABC Research Group, 1999). By explicitly modeling these three phases we are able to test their relative contribution to strategy success in different social environmental structures. Overall, a general characteristic shared by many social learning strategies, including those we study here, is that they alter the structure of the social environment by increasing the frequency of the correct option (i.e. the one with the highest payoff) and simultaneously decreasing the diversity of options in the group. This is a result of their bias towards specific sources (best member, majority) and their selectiveness (e.g. copy only if payoff better) 1 . This property has been extensively studied in the context of biased cultural transmission (Boyd & Richerson, 1985) and suggests a key factor influencing strategy success in a changing environment: the speed with which they increase the frequency of the correct option in the group and, therefore, their ability to respond to environmental change. Our goal here is to show how this speed can be influenced by the strategy’s building blocks (their sampling and decision rule) and by the structure and efficiency of the social network. In what follows we derive specific expectations, based on previous literature and preliminary analytic calculations, One can relax this assumption if other selective forces (e.g. natural selection) are at work.