A Semantic Framework For Socially Adaptive Agents Towards Strong Norm Compliance

We address the question of how an agent can adapt its behavior to comply with newly adopted norms. This is particularly relevant in the case of open systems where agents may enter and leave norm-governed social contexts not known at design time. This requires norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior.We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its norm compliance properties. A weak form of norm compliance allows agents to abort execution in order to prevent norm violation. In this paper we investigate a stronger notion of norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be strongly compliant with any arbitrary set of norms. We then investigate situations when strong norm compliance can be guaranteed.