  The emergence of mutual knowledge is a major cognitive mechanism for the
robustness of complex socio technical systems. It has been extensively studied
from an ethnomethodological point of view and empirically reproduced by multi
agent simulations. Whilst such simulations have been used to design real work
settings the underlying theoretical grounding for the process is vague. The aim
of this paper is to investigate whether the emergence of mutual knowledge (MK)
in a group of co-located individuals can be explained as a percolation
phenomenon. The followed methodology consists in coupling agent-based
simulation with dynamic networks analysis to study information propagation
phenomena: after using an agent-based simulation we generated and then analysed
its traces as networks where agents met and exchanged knowledge. Deep analysis
of the resulting networks clearly shows that the emergence of MK is comparable
to a percolation process. We specifically focus on how changes at the
microscopic level in our agent based simulator affect percolation and
robustness. These results therefore provides theoretical basis for the analysis
of social organizations.
