{"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/efficiently-checking-actual-causality-with","title":"Efficiently Checking Actual Causality with SAT Solving","arxiv_id":"1904.13101","date":"2019-04-30","proceeding":null,"authors":["Amjad Ibrahim","Simon Rehwald","Alexander Pretschner"],"abstract":"Recent formal approaches towards causality have made the concept ready for\nincorporation into the technical world. However, causality reasoning is\ncomputationally hard; and no general algorithmic approach exists that\nefficiently infers the causes for effects. Thus, checking causality in the\ncontext of complex, multi-agent, and distributed socio-technical systems is a\nsignificant challenge. Therefore, we conceptualize an intelligent and novel\nalgorithmic approach towards checking causality in acyclic causal models with\nbinary variables, utilizing the optimization power in the solvers of the\nBoolean Satisfiability Problem (SAT). We present two SAT encodings, and an\nempirical evaluation of their efficiency and scalability. We show that\ncausality is computed efficiently in less than 5 seconds for models that\nconsist of more than 4000 variables.","url_abs":"http://arxiv.org/abs/1904.13101v1","url_pdf":"http://arxiv.org/pdf/1904.13101v1.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":"efficiently-checking-actual-causality-with","repo_url":"https://github.com/amjadKhalifah/HP2SAT1.0","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}