  The question how social norms can emerge from microscopic interactions
between individuals is a key problem in social sciences to explain collective
behavior. In this paper we propose an agent-based model to show that randomly
distributed social behavior by way of local interaction converges to a state
with a multimodal distribution of behavior. This can be interpreted as a
coexistence of different social norms, a result that goes beyond previous
investigations. The model is discrete in time and space, behavior is
characterized in a continuous state space. The adaptation of social behavior by
each agent is based on attractive and repulsive forces caused by friendly and
adversary relations among agents. The model is analyzed both analytically and
by means of spatio-temporal computer simulations. It provides conditions under
which we find convergence towards a single norm, coexistence of two opposing
norms, and coexistence of a multitude of norms. For the latter case, we also
show the evolution of the spatio-temporal distribution of behavior.
