Streamliners for Answer Set Programming
Published in Proceedings of the 42nd International Conference on Logic Programming (ICLP 2026), 2026
Languages for Knowledge Representation and Reasoning, such as ASP, CP, and SMT, excel at solving some complex problems, but encoding them into a higher-level language may be more profitable, leaving these formalisms as targets for solving. Recent studies aim to convert controlled natural languages into formal representations, yet these solutions are often tailored to specific languages and require significant effort. This paper introduces a general framework that generates grammars for target representation languages, enabling the translation of problems stated in CNL into formal representations. The related system, CNLWizard, offers a flexible, high-level approach to defining desired grammars, significantly reducing the time and effort needed to create custom grammars. Finally, we demonstrate the system’s effectiveness through an experimental analysis.
Citation: Voboril, F.; Gebser, M.; Szeider S.; and Tarzariol, A. (2026). "Streamliners for Answer Set Programming". In Proceedings 42nd International Conference on Logic Programming, (ICLP 2026), Electronic Proceedings in Theoretical Computer Science, 450 (pp. 236–255).