Collective Learning and Information Diffusion for Efficient Emergence of Social Norms

Abstract

Social norms are believed to be the main cause of evolution and establishment of many complex systems in human societies, ranging from language lexicon systems to cultural codes of conduct. Revelation of mechanisms behind the emergence of social norms can not only provide us with a better understanding of formation and evolution processes of opinions, conventions and rules in human societies, but more importantly enable us to build and control large-scale complex systems. In this paper, a theoretical framework is proposed to study the emergence of social norms based on agent collective learning and information diffusion in complex relationship networks. In this framework, agents learn collectively from local interactions with their neighbors using multiagent learning methods, and diffuse their learnt information based on their underlying relationships. Extensive experiments are carried out to test the proposed framework in different topological and environmental settings and experimental results show that the framework is effective for emergence of social norms in complex relationship networks. The proposed framework emulates the opinion aggregation and knowledge transfer process in human and the research findings reveal some significant insights into efficient mechanisms of norm emergence in complex relationship networks.