Multi-user Norm Consensus.

Many agents act in environments with multiple human users, from care robots to smart assistants. When interacting in multi-user environments it is paramount that these agents act as all users expect. However, it is not always possible to have well-defined collective preferences, nor to easily infer them from individual preferences. This is especially true in fast changing environments, like a device placed in a public space where users can enter and exit freely. In response, this paper proposes a model to represent individual preferences about the behaviour of an agent and a mechanism to find multi-user consensuses over these preferences. Norms can then be generated to ensure that when the agent follows them it will act according to the preferences of all users. We formalise what a consensus norm is and what properties the set of consensus norms should satisfy (i.e. generate the minimum number of norms while maximising the coverage of user preferences). We provide an optimisation approach to find this set of norms and show that our approach satisfies the aforementioned properties.