Towards Monitoring of Group Interactions and Social Roles via Overhearing

We are investigating how to provide intelligent, pervasive support of group of people within so-called "smart environments". Our current main assumption, based on literature in psychology and organizational studies, is that a group performs some complex, routine task as a structured activity, that is, by following some protocols that allow its members to coordinate and share a common understanding about the current progress towards the group's goal and the roles currently played by each member. If this is the case, a condition to provide support to a group activity by artificial agents is to share the same understanding. To this end, we have identified two initial goals: first, being able to understand if a group activity is progressing with respect to its expected evolution, by analyzing what is happening within the smart environment; second, recognizing what are the social roles of the group members, taking in mind that these are not necessarily pre-assigned and may change in time. This paper sketches a preliminary approach to these issues and a computational model for an overhearer agent. We suggest a preliminary set of rules for conversation analysis and social role recognition, and validate them against the simple case of "implicit organizations", which - being artificial - follow well-known protocols