The Physics of Social Evolution and Collective Intelligence

Historical experience shows that intellectual achievements are attributable to the evolution of civilization rather than the expansion of super-brains. Collective intelligence therefore represents an important direction for the next generation of artificial intelligence. How can individuals unite to give rise to collective order and thereby generate more intelligence? This has long been a core question jointly explored by complexity science, including evolutionary game theory, opinion dynamics, epidemic dynamics, and human mobility patterns. At the same time, research on these social dynamics is closely linked to a physical perspective, such as the spatial clustering of cooperation, the diffusion of opinions, phase transitions in epidemic spreading, and the physical laws governing human mobility. Benefiting from the tools of statistical physics, including agent-based modeling, network theory, and dynamical systems analysis, these research areas have made substantial progress over the past several decades, revealing universal patterns that recur across otherwise unrelated social phenomena.This Research Topic aims to advance the latest progress in social evolution from the perspective of collective intelligence. The next generation of artificial intelligence should not be confined to a subfield of computer science, but should encompass all interdisciplinary fields that help uncover the mechanisms underlying intelligence. We therefore welcome submissions from all disciplines that apply physical and complexity-science perspectives to understanding how collective order and intelligence emerge from individual interactions. A central challenge is identifying the mechanisms that allow simple, locally interacting agents, whether humans, animals, or artificial systems, to self-organize into structures capable of solving problems no single agent could solve alone. By bringing together researchers working on cooperation, opinion formation, epidemic spreading, and human mobility, this Research Topic seeks to build a unified physical understanding of how collective intelligence arises, persists, and can be harnessed to inform the design of future AI systems.This Research Topic welcomes original research articles, reviews, mini reviews, and perspective papers that apply physical and complexity-science approaches to the study of social evolution and collective intelligence. Both theoretical and empirical or data-driven studies are welcome. Topics of interest include, but are not limited to:• Strategy evolution, including evolutionary game theory and the emergence of cooperation • Opinion evolution and dynamics in social systems • Epidemic evolution, including spreading dynamics and phase transitions • Human mobility patterns and their physical laws • Collective and social intelligence • AI-supported systems for modeling social and collective behavior • Network structure and dynamics in social systems • Other topics related to social evolution and collective intelligence Topic editors: Chaoqian Wang, Xin Lu, Attila Szolnoki Source: https://www.frontiersin.org/research-topics/84860/the-physics-of-social-evolution-and-collective-intelligence