{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/modeling-variations-of-first-order-horn","title":"Modeling Variations of First-Order Horn Abduction in Answer Set Programming","arxiv_id":"1512.08899","date":"2015-12-30","proceeding":null,"authors":["Peter Schüller"],"abstract":"We study abduction in First Order Horn logic theories where all atoms can be\nabduced and we are looking for preferred solutions with respect to three\nobjective functions: cardinality minimality, coherence, and weighted abduction.\nWe represent this reasoning problem in Answer Set Programming (ASP), in order\nto obtain a flexible framework for experimenting with global constraints and\nobjective functions, and to test the boundaries of what is possible with ASP.\nRealizing this problem in ASP is challenging as it requires value invention and\nequivalence between certain constants, because the Unique Names Assumption does\nnot hold in general. To permit reasoning in cyclic theories, we formally\ndescribe fine-grained variations of limiting Skolemization. We identify term\nequivalence as a main instantiation bottleneck, and improve the efficiency of\nour approach with on-demand constraints that were used to eliminate the same\nbottleneck in state-of-the-art solvers. We evaluate our approach experimentally\non the ACCEL benchmark for plan recognition in Natural Language Understanding.\nOur encodings are publicly available, modular, and our approach is more\nefficient than state-of-the-art solvers on the ACCEL benchmark.","url_abs":"http://arxiv.org/abs/1512.08899v4","url_pdf":"http://arxiv.org/pdf/1512.08899v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"modeling-variations-of-first-order-horn","repo_url":"https://bitbucket.org/knowlp/asp-fo-abduction","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"natural-language-understanding","task_name":"Natural Language Understanding"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}