  We present a model for studying communities of epistemically interacting
agents who update their belief states by averaging (in a specified way) the
belief states of other agents in the community. The agents in our model have a
rich belief state, involving multiple independent issues which are interrelated
in such a way that they form a theory of the world. Our main goal is to
calculate the probability for an agent to end up in an inconsistent belief
state due to updating (in the given way). To that end, an analytical expression
is given and evaluated numerically, both exactly and using statistical
sampling. It is shown that, under the assumptions of our model, an agent always
has a probability of less than 2% of ending up in an inconsistent belief state.
Moreover, this probability can be made arbitrarily small by increasing the
number of independent issues the agents have to judge or by increasing the
group size. A real-world situation to which this model applies is a group of
experts participating in a Delphi-study.
