{"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/theoretical-robopsychology-samu-has-learned","title":"Theoretical Robopsychology: Samu Has Learned Turing Machines","arxiv_id":"1606.02767","date":"2016-06-08","proceeding":null,"authors":["Norbert Bátfai"],"abstract":"From the point of view of a programmer, the robopsychology is a synonym for\nthe activity is done by developers to implement their machine learning\napplications. This robopsychological approach raises some fundamental\ntheoretical questions of machine learning. Our discussion of these questions is\nconstrained to Turing machines. Alan Turing had given an algorithm (aka the\nTuring Machine) to describe algorithms. If it has been applied to describe\nitself then this brings us to Turing's notion of the universal machine. In the\npresent paper, we investigate algorithms to write algorithms. From a pedagogy\npoint of view, this way of writing programs can be considered as a combination\nof learning by listening and learning by doing due to it is based on applying\nagent technology and machine learning. As the main result we introduce the\nproblem of learning and then we show that it cannot easily be handled in\nreality therefore it is reasonable to use machine learning algorithm for\nlearning Turing machines.","url_abs":"http://arxiv.org/abs/1606.02767v2","url_pdf":"http://arxiv.org/pdf/1606.02767v2.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":"theoretical-robopsychology-samu-has-learned","repo_url":"https://github.com/nbatfai/SamuCTuring","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"theoretical-robopsychology-samu-has-learned","repo_url":"https://github.com/nbatfai/SamuTuring","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"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}