Norms have become a common mechanism to regulate the behavior of agents in multi-agent systems (MAS). However, establishing a stable set of norms is not trivial, particularly in dynamic environments, under changing (and unpredictable) conditions.

We propose a computational model that facilitates agents in a MAS to collaboratively evolve their norms, reconfigure themselves, to adapt to changing conditions. Our approach borrows from the social contagion phenomenon to exploit the notion of positive infection: agents with good behaviors become infectious to spread their norms in the agent society. By combining infection and innovation, a mechanism allowing agents exploring new norms, our computational model helps MAS to continuously stabilize despite perturbations.