In this paper, we introduce a probabilistic relational data model as the basis for developing multi-agent probabilistic reasoning systems. Since our model subsumes the traditional relational data model, it immediately follows that we can take full advantage of the existing distributed and concurrency control techniques to address the undesirable characteristics exhibited by current multi-agent probabilistic reasoning systems. Thereby, our probabilistic relational data model has important theoretical and practical rami cations. One uni ed model allows the cross-fertilization of techniques, and serves as a basis for implementing one system for both of these similar domains.
Cory J. Butz, S. K. Michael Wong