An empirical semantics approach to reasoning about communication ?
When designing multiagent systems, one can often avail of an existing specification of communication rules (in the form of protocols, ACL semantics, etc.). The question that then arises naturally is how to design appropriate agents to operate on such a specification. Moreover, if the multiagent system in question exhibits the characteristics of an open system, the problem is complicated even further by the fact that adherence to a supposedly agreed specification cannot be ensured on the side of other agents. This paper presents an architecture for dealing with a generic type of pre-specified communication patterns (containing surface structure and logical constraint specifications) based on an empirical semantics model of communication. By combining existing expectations about the use of communication with empirical observation, this model allows for a flexible adaptation to evolving communication semantics. The architecture itself is based on the InFFrAsocial reasoning framework and the concept of interaction frames. When interpreted according to the empirical semantics approach, interaction frames that represent classes of interaction situations can be used to conduct decision-theoretic reasoning about communication. After introducing the abstract architecture and giving a formal model for its probabilistic semantics, the results of an experimental validation of the approach in a complex domain are presented to illustrate its effectiveness.
agent interaction agent communication languages interaction protocols multiagent learning social reasoning