A categorization of simulation works on norms

Abstract

In multi-agent systems, software agents are modelled to possess characteristics and behaviour borrowed from human societies. Norms are expectations of behaviours of the agents in a society. Norms can be established in a society in different ways. In human societies, there are several types of norms such as moral norms, social norms and legal norms (laws). In artificial agent societies, the designers can impose these norms on the agents. Being autonomous, agents might not always follow the norms. Monitoring and controlling mechanisms should be in place to enforce norms. As the agents are autonomous, they themselves can evolve new norms while adapting to changing needs. In order to design and develop robust artificial agent societies, it is important to understand different approaches proposed by researchers by which norms can spread and emerge within agent societies. This paper makes two contributions to the study of norms. Firstly, based on the simulation works on norms, we propose a life-cycle model for norms. Secondly, we discuss different mechanisms used by researchers to study norm creation, spreading, enforcement and emergence.