A model building framework for Answer Set Programming with external computations
Thomas Eiter, Michael Fink, Giovambattista Ianni, Thomas Krennwallner,, Christoph Redl, Peter Sch\"uller

TL;DR
This paper introduces a flexible, scalable framework for evaluating answer set programs with external sources, significantly improving performance by dividing programs into smaller parts and interleaving external computation with model building.
Contribution
It proposes a novel, configurable evaluation framework using evaluation and model graphs, enhancing scalability and efficiency for HEX-programs and related formalisms.
Findings
Significant performance improvements over previous methods
Framework effectively handles large, complex external sources
Prototype demonstrates practical scalability and flexibility
Abstract
As software systems are getting increasingly connected, there is a need for equipping nonmonotonic logic programs with access to external sources that are possibly remote and may contain information in heterogeneous formats. To cater for this need, HEX programs were designed as a generalization of answer set programs with an API style interface that allows to access arbitrary external sources, providing great flexibility. Efficient evaluation of such programs however is challenging, and it requires to interleave external computation and model building; to decide when to switch between these tasks is difficult, and existing approaches have limited scalability in many real-world application scenarios. We present a new approach for the evaluation of logic programs with external source access, which is based on a configurable framework for dividing the non-ground program into possibly…
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