  The Category Game is a multi-agent model that accounts for the emergence of
shared categorization patterns in a population of interacting individuals. In
the framework of the model, linguistic categories appear as long lived
consensus states that are constantly reshaped and re-negotiated by the
communicating individuals. It is therefore crucial to investigate the long time
behavior to gain a clear understanding of the dynamics. However, it turns out
that the evolution of the emerging category system is so slow, already for
small populations, that such an analysis has remained so far impossible. Here,
we introduce a fast no-rejection algorithm for the Category Game that
disentangles the physical simulation time from the CPU time, thus opening the
way for thorough analysis of the model. We verify that the new algorithm is
equivalent to the old one in terms of the emerging phenomenology and we
quantify the CPU performances of the two algorithms, pointing out the neat
advantages offered by the no-rejection one. This technical advance has already
opened the way to new investigations of the model, thus helping to shed light
on the fundamental issue of categorization.
