Relational Information Exchange and Aggregation in Multi-Context Systems

Multi-Context Systems (MCSs) are a powerful framework for representing the information exchange between heterogeneous (possibly nonmonotonic) knowledge-bases. Significant recent advancements include implementations for realizing MCSs, e.g., by a distributed evaluation algorithm and corresponding optimizations. However, certain enhanced modeling concepts like aggregates and the use of variables in bridge rules, which allow for more succinct representations and ease system design, have been disregarded so far. We fill this gap introducing open bridge rules with variables and aggregate expressions, extending the semantics of MCSs correspondingly. The semantic treatment of aggregates allows for alternative definitions when so-called grounded equilibria of an MCS are considered. We discuss options in relation to well-known aggregate semantics in answer-set programming. Moreover, we develop an implementation by elaborating on the DMCS algorithm, and report initial experimental results.