{"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/dynamical-kinds-and-their-discovery","title":"Dynamical Kinds and their Discovery","arxiv_id":"1612.04933","date":"2016-12-15","proceeding":null,"authors":["Benjamin C. Jantzen"],"abstract":"We demonstrate the possibility of classifying causal systems into kinds that\nshare a common structure without first constructing an explicit dynamical model\nor using prior knowledge of the system dynamics. The algorithmic ability to\ndetermine whether arbitrary systems are governed by causal relations of the\nsame form offers significant practical applications in the development and\nvalidation of dynamical models. It is also of theoretical interest as an\nessential stage in the scientific inference of laws from empirical data. The\nalgorithm presented is based on the dynamical symmetry approach to dynamical\nkinds. A dynamical symmetry with respect to time is an intervention on one or\nmore variables of a system that commutes with the time evolution of the system.\nA dynamical kind is a class of systems sharing a set of dynamical symmetries.\nThe algorithm presented classifies deterministic, time-dependent causal systems\nby directly comparing their exhibited symmetries. Using simulated, noisy data\nfrom a variety of nonlinear systems, we show that this algorithm correctly\nsorts systems into dynamical kinds. It is robust under significant sampling\nerror, is immune to violations of normality in sampling error, and fails\ngracefully with increasing dynamical similarity. The algorithm we demonstrate\nis the first to address this aspect of automated scientific discovery.","url_abs":"http://arxiv.org/abs/1612.04933v1","url_pdf":"http://arxiv.org/pdf/1612.04933v1.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":"dynamical-kinds-and-their-discovery","repo_url":"https://github.com/jantzen/eugene","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"scientific-discovery","task_name":"scientific discovery"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}