Enhancing social cohesion with cooperative bots in societies of greedy, mobile individuals
Addressing collective issues in social development requires a high level of social cohesion, characterized by cooperation and close social connections. However, social cohesion is challenged by selfish, greedy individuals. With the advancement of artificial intelligence (AI), the dynamics of human-machine hybrid interactions introduce new complexities in fostering social cohesion. This study explores the impact of simple bots on social cohesion from the perspective of human-machine hybrid populations within network. By investigating collective self-organizing movement during migration, results indicate that cooperative bots can promote cooperation, facilitate individual aggregation, and thereby enhance social cohesion. The random exploration movement of bots can break the frozen state of greedy population, help to separate defectors in cooperative clusters, and promote the establishment of cooperative clusters. However, the presence of defective bots can weaken social cohesion, underscoring the importance of carefully designing bot behavior. Our research reveals the potential of bots in guiding social self-organization and provides insights for enhancing social cohesion in the era of human-machine interaction within social networks.
Recent research has sparked interest in using AI-driven agents or bots to study cooperation issues [38, 39]. They have revealed bots’ ability to address coordination dilemmas [21] and scaffold cooperation [23] by integrating bots into network engineering and game interactions [22, 24]. Here, our focus extends beyond the influence of bots on individual cooperation to their role in the collective self-organization movements within populations.
these cooperative bots can facilitate cooperation and fostering spatial clustering within mobile populations, thereby promoting highly social cohesion. Interestingly, cooperative bots can break the population out of its frozen state, stimulating the self-organization movement among selfish, greedy individuals. The emergence and maintenance of social cohesion in sparse mobile populations have often been a challenge in human-human interactions, but the introduction of cooperative bots can solve this challenge situation in such hybrid populations. Therefore, our study reveal the potential of simple cooperative bots in guiding individual behavior to address collective issues.
Initially, the random spatial distribution impedes the survival of isolated cooperators, leading to a decline in the fraction of cooperation (FC) in the early stages of evolution. When migration is feasible, cooperative migration further drives the aggregation into clusters, compared to the cluster formation process without migration as discussed in