Representational Exchange in Human Social Learning

Particle Swarm Optimization (PSO) is a widely used metaheuristic approach for solving optimization problems. Recent developments in this field involve the adaptation of human learning behaviors to enhance algorithmic performance. One such adaptation is the Adaptive Particle Swarm Optimization based on Human Social Learning (APSO-HSL), a variant of PSO that incorporates human inspired learning strategies. This study aims to enhance the performance of APSO-HSL on the Traveling Salesman Problem (TSP) by incorporating additional human learning strategies. The proposed algorithm, named Modified Adaptive Particle Swarm Optimization–Human Learning Strategies (MAPSO-HLS), integrates learning mechanisms from Human Learning Optimization (HLO), including individual, random, and social learning. This research is classified as applied research and algorithmic experimentation, focusing on the development and modification of a metaheuristic algorithm to solve a well-known combinatorial optimization problem. Benchmark datasets from the Traveling Salesman Problem Library (TSPLIB) are used for evaluation, and all computations and experiments are implemented in Python. The performance of MAPSO-HLS is compared with the exact method in terms of shortest distance and computation time. The results of the study indicate that the MAPSO-HLS algorithm is capable of producing TSP solutions with low total distance deviation, below 10%, compared to exact solutions across all tested datasets. This reflects a high level of solution accuracy. In addition, MAPSO-HLS demonstrates better time efficiency than the exact ILP method, particularly for datasets with a large number of cities. The integration of human learning strategies within the adaptive PSO framework provides significant advantages in terms of both efficiency and effectiveness in solving TSP.

Higher levels of both individual education and community education may facilitate improved sexual and reproductive health knowledge, but our understanding of this relationship in sub-Saharan Africa remains limited. Drawing on human capital and social learning theories, and Demographic Health Survey data from Uganda, we examine the independent and interactive associations between individual and community education and two outcomes—HIV prevention knowledge and knowledge of different contraceptive methods—including differences by gender. Consistent with human capital and social learning theories, results from multilevel regression models show that both individual education and community education levels are independently and positively associated with more accurate sexual and reproductive health knowledge. Further, in support of the idea that human capital and social learning theories work in tandem, we find that the association between individual education and HIV knowledge is stronger in less educated communities, and grows weaker as community education increases, for both men and women. Similarly, for men, but not women, the association between individual education and contraceptive knowledge is stronger in less educated communities and weaker as community education increases. Among women, individual education was strongly and positively associated with contraceptive knowledge, an association that varied little across more or less educated communities. Our findings suggest that policy makers should consider community education levels when developing priorities for sexual and reproductive health knowledge interventions.

The Middle Stone Age record of southern Africa provides evidence for the origins and evolution of complex social relationships, and potentially qualities like humility, wisdom, and grace that helped humans navigate these complex social relationships. Homo sapiens first appear in Africa ~200,000–150,000 years ago during the Middle Stone Age. While there are anatomical changes that mark the speciation of Homo sapiens, they are not associated with major technological or behavioural changes. Instead, the archaeological record documents spatially and temporally discontinuous variation in social learning mechanisms and sociality. Here, recent evidence is reviewed in the Middle Stone Age of southern Africa, between ~500,000 and ~50,000 years ago. Evidence for early human social learning and sociality derives from studies on how stone tools are manufactured, how far stone raw material is moved across the landscape, and the material evidence for symbolling, such as brightly coloured ochre and incised objects. Stone tool technologies during some periods in the Middle Stone Age are consistent with an increased emphasis on imitative social learning, which could be associated with the need to communicate group membership by replicating the behaviours of others, and/or with increased self-regulation. For other periods in the Middle Stone Age, variation in stone tool manufacturing strategies suggest more emphasis on emulative, rather than imitative, social learning, which may be linked to behavioural plasticity and innovation. Stone raw material is sometimes transported long distances, which could be indicative of inter-group interaction. At many sites, however, evidence for the long-distance transfer of stone raw materials is lacking. Ochre and incised objects are common in some Middle Stone Age contexts, but rare in others. It is suggested that the nature of human social learning and sociality changed through the Middle Stone Age, and in many cases these changes did not occur in a temporally vectored manner. This synthesis is not consistent with models of human cognition that emphasize behavioural or cognitive progression over time. The archaeological record to date suggests that at least some human capacities for navigating complex social relationships may have been present at the onset of the Middle Stone Age before the origins of Homo sapiens, and they are variably expressed through time.

There has been much progress in understanding human social learning, including recent studies integrating social information into the reinforcement learning framework. Yet previous studies often assume identical payoffs between observer and demonstrator, overlooking the diversity of social information in real-world interactions. We address this gap by introducing a socially correlated bandit task that accommodates payoff differences among participants, allowing for the study of social learning under more realistic conditions. Our Social Generalization (SG) model, tested through evolutionary simulations and two online experiments, outperforms existing models by incorporating social information into the generalization process, but treating it as noisier than individual observations. Our findings suggest that human social learning is more flexible than previously believed, with the SG model indicating a potential resource-rational trade-off where social learning partially replaces individual exploration. This research highlights the flexibility of humans' social learning, allowing us to integrate social information from others with different preferences, skills, or goals.

The past 2 Myr have seen both unprecedented environmental instability and the evolution of the human capacity for complex culture. This, along with the observation that cultural evolution occurs faster than genetic evolution, has led to the suggestion that culture is an adaptation to an unstable environment. We test this hypothesis by examining the ability of human social learning to respond to environmental changes. We do this by inserting human participants (n = 4800) into evolutionary simulations with a changing environment while varying the social information available to individuals across five conditions. We find that human social learning shows some signs of adaptation to environmental instability, including critical social learning, the adoption of up-and-coming traits and, unexpectedly, contrariness. However, these are insufficient to avoid significant fitness declines when the environment changes, and many individuals are highly conformist, which exacerbates the fitness effects of environmental change. We conclude that human social learning reflects a compromise between the competing needs for flexibility to accommodate environmental change and fidelity to accurately transmit valuable cultural information.

Through learning from others and sharing what we know in our everyday social interactions, we learn things that go far beyond what we can directly experience. What makes human social learning so distinctive, powerful, and effective? This chapter reviews recent developmental evidence on how our understanding of others—basic aspects of human social cognition—can support effective learning and communication. Even at a young age, humans show remarkable abilities to reason about others’ minds to (1) draw sophisticated inferences from information provided by others, (2) use such information to evaluate others’ informativeness, and (3) actively teach and communicate information to others. These studies suggest that human social learning is rooted in the basic social-cognitive abilities to understand what others want, need, and know, as well as what is useful or costly for others. Such abilities allow even young children to make flexible and rational decisions to learn from others and teach others, providing foundations for the development of distinctively human social learning.

The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.

Inferential social learning: cognitive foundations of human social learning and teaching.

Learning from other minds: an optimistic critique of reinforcement learning models of social learning

Downes, Gerrans, and Sutton all raise important issues for the account of human social learning and cooperation developed in The Evolved Apprentice. Downes suggests that I have bought too uncritically into the view that hunting was economically critical to forager life; I remain unpersuaded, while conceding something to the alternative view that hunting was signaling. Downes also suggests that I consider extending the evolved apprentice model to contemporary issues in social epistemology; I wonder whether that might make the model so general that it loses explanatory force. Gerrans probes the model on the relationship between social learning and imitation; I respond by arguing that imitation became important relatively late in the human social learning career, probably via learning to communicate via gesture. Sutton wonders whether the model of social learning developed is too intellectualist and individualist; I respond by emphasizing the varied task demands in different domains, and the change over time of the different elements involved in social learning.

Rational conformity behavior in social learning promotes cooperation in spatial public goods game

**Author(s):** Schimmelpfennig, R; Ehret, S; Voigt, S; Efferson, C Theoretical and empirical research suggests that human social learning is both frequency- and payoff-dependent. Less evidence exists about the joint effect of both types of social information. We ran a two-staged incentivised online experiment in Kenya (N=1400). First, participants were ranked based on their performance in a Raven Matrices Task. Second, participants were grouped to make decisions in a sequential task in which participants receive a private signal and can observe the decisions of upstream participants. In a 2x2 factorial design, we manipulated whether high-performing participants would make their decisions early or late in the sequence and whether participants are informed about the ordering or not. We find strong evidence for frequency-dependent social learning across all conditions. However, while frequency- and payoff-dependent cues interact to increase the accuracy of decisions, we don’t find any significant interaction effect on social learning. To understand how learning shapes decisions in complex real-world scenarios, research should further investigate the joint effects of social learning biases for decision-making.

The evolution of conformist transmission in social learning when the environment changes periodically

Developmental research on selective social learning, or 'social learning strategies', is currently a rich source of information about when children copy behaviour, and who they prefer to copy. It also has the potential to tell us when and how human social learning becomes cultural learning; i.e. mediated by psychological mechanisms that are specialized, genetically or culturally, to promote cultural inheritance. However, this review article argues that, to realize its potential, research on the development of selective social learning needs more clearly to distinguish functional from mechanistic explanation; to achieve integration with research on attention and learning in adult humans and 'dumb' animals; and to recognize that psychological mechanisms can be specialized, not only by genetic evolution, but also by associative learning and cultural evolution.

We propose that human social learning is subject to a trade-off between the cost of performing a computation and the flexibility of its outputs. Viewing social learning through this lens sheds light on cases that seem to violate bifocal stance theory (BST) - such as high-fidelity imitation in instrumental action - and provides a mechanism by which causal insight can be bootstrapped from imitation of cultural practices.