In many occasions of our daily lives, we want to spontaneously interact with nearby strangers for sharing ideas, chatting, saving time/money, or helping each other. For that purpose, it is necessary to identify shared context situations that depend on distributed sources of users local context. So far, most of the work that investigates mechanisms to support spontaneous discovery and interaction among mobile users has not yet explored means of automatic detection of common Global Context States (GCS). In this paper, we propose a distributed reasoning approach and algorithm that determines a distributed Global Context State among potentially interacting nodes/peers. We also evaluate the complexity of the algorithm - through simulation - and identify that the convergence of the algorithm depends very much on the users mobility pattern and the requested minimum number of contributing peers, rather than on the volatility of the local contexts.