Evolution of Human-Like Social Grooming Strategies Regarding Richness and Group Size

Abstract

Human social strategies have evolved as an adaption to behave in complex societies. In such societies, humans intensively tend to cooperate with their closer friends, because they have to distribute their limited resources through cooperation (e.g., time, food, etc.). It also makes the situation difficult to have uniform social relationships (social grooming) with all friends. Thus, the social relationship strengths often show a much skewed distribution (a power law distribution). Here we aim to show adaptivity of such social grooming strategies in order to explore the evolution of human social intelligence. We use a model in the framework of evolutionary games where the social grooming strategies evolve via building social relationships with cooperators. Simulation results demonstrate four evolutionary trends. One of the trends is similar to the strategy that humans use. We find that these trends depend on three parameters; individuals' richness, group sizes, and the amount of social grooming. The human-like strategy evolves in large poor groups. Moreover, the increase of the amount of social grooming makes the group size larger. Conversely, this implies that the same strategy evolves when the amount of social grooming is properly adjusted even if the group sizes are different. Our results are important in the sense that, between human and non-human primates, the differences of the group size and the amount of social grooming are significant.

On the Modeling and Verification of Collective and Cooperative Systems

“…Cooperation activities and collective behaviors are widespread phenomena in several environments, ranging from nature to human social relationships and artificial systems. Therefore, they have cross-cutting implications in different specific fields of knowledge, including, just to cite a few, biology ( Crall et al, 2019 ; Glen et al, 2019 ; Romanov et al, 2022 ), sociology ( Takano and Ichinose, 2018 ; Will et al, 2020 ), and robotics ( Dai et al, 2016 ; Rausch et al, 2020 ; Mehmood et al, 2021 ). Although different levels of abstraction are involved, information sharing mechanisms form the base for the evolution of biological, social, and engineering systems exhibiting the behaviors specified above.…”

Multiple learning mechanisms promote cooperation in public goods games with project selection

“…Different from the frequently discussed punishment mechanisms where the punishers have to face severe retaliations from the punished, in real society, there exists a kind of scenario, called gain all-or-nothing activity, where the free-rider problems may be effectively avoided [33,34]. For exam-ple, moving a huge boulder in the way needs sufficient contributions from all the group members, or else, no one has the opportunity to go through the blocked mountain road.…”