The Stable Model Semantics for Higher-Order Logic Programming
This work addresses the need for a formal semantics in higher-order logic programming, potentially enabling novel Answer Set Programming systems, though it is incremental as it builds on existing theories.
The authors tackled the problem of defining a stable model semantics for higher-order logic programs, using Approximation Fixpoint Theory to generalize classical stable models and retain desirable properties, while also deriving alternative semantics like supported and well-founded models for free.
We propose a stable model semantics for higher-order logic programs. Our semantics is developed using Approximation Fixpoint Theory (AFT), a powerful formalism that has successfully been used to give meaning to diverse non-monotonic formalisms. The proposed semantics generalizes the classical two-valued stable model semantics of (Gelfond and Lifschitz 1988) as-well-as the three-valued one of (Przymusinski 1990), retaining their desirable properties. Due to the use of AFT, we also get for free alternative semantics for higher-order logic programs, namely supported model, Kripke-Kleene, and well-founded. Additionally, we define a broad class of stratified higher-order logic programs and demonstrate that they have a unique two-valued higher-order stable model which coincides with the well-founded semantics of such programs. We provide a number of examples in different application domains, which demonstrate that higher-order logic programming under the stable model semantics is a powerful and versatile formalism, which can potentially form the basis of novel ASP systems.