Abstract:

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.

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