Query Answering in Nondeterministic, Nonmonotonic Logic Databases

We consider in this paper an extension of Datalog with mechanisms for temporal, non monotonic and non deterministic reasoning, which we refer to as Datalog++. We show, by means of examples, its flexibility in expressing queries of increasing difficulty, up to aggregates and data cube. Also, we show how iterated fixpoint and stable model semantics can be combined to the purpose of clarifying the semantics of Datalog++ programs, and supporting their efficient execution. On this basis, the design of appropriate optimization techniques for Datalog++ is also briefly discussed.