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.