{"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/feynman-machine-the-universal-dynamical","title":"Feynman Machine: The Universal Dynamical Systems Computer","arxiv_id":"1609.03971","date":"2016-09-13","proceeding":null,"authors":["Eric Laukien","Richard Crowder","Fergal Byrne"],"abstract":"Efforts at understanding the computational processes in the brain have met\nwith limited success, despite their importance and potential uses in building\nintelligent machines. We propose a simple new model which draws on recent\nfindings in Neuroscience and the Applied Mathematics of interacting Dynamical\nSystems. The Feynman Machine is a Universal Computer for Dynamical Systems,\nanalogous to the Turing Machine for symbolic computing, but with several\nimportant differences. We demonstrate that networks and hierarchies of simple\ninteracting Dynamical Systems, each adaptively learning to forecast its\nevolution, are capable of automatically building sensorimotor models of the\nexternal and internal world. We identify such networks in mammalian neocortex,\nand show how existing theories of cortical computation combine with our model\nto explain the power and flexibility of mammalian intelligence. These findings\nlead directly to new architectures for machine intelligence. A suite of\nsoftware implementations has been built based on these principles, and applied\nto a number of spatiotemporal learning tasks.","url_abs":"http://arxiv.org/abs/1609.03971v1","url_pdf":"http://arxiv.org/pdf/1609.03971v1.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":"feynman-machine-the-universal-dynamical","repo_url":"https://github.com/ogmacorp/OgmaNeo","is_official":0,"mentioned_in_paper":0,"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}