{"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/markov-brains-a-technical-introduction","title":"Markov Brains: A Technical Introduction","arxiv_id":"1709.05601","date":"2017-09-17","proceeding":null,"authors":["Arend Hintze","Jeffrey A. Edlund","Randal S. Olson","David B. Knoester","Jory Schossau","Larissa Albantakis","Ali Tehrani-Saleh","Peter Kvam","Leigh Sheneman","Heather Goldsby","Clifford Bohm","Christoph Adami"],"abstract":"Markov Brains are a class of evolvable artificial neural networks (ANN). They\ndiffer from conventional ANNs in many aspects, but the key difference is that\ninstead of a layered architecture, with each node performing the same function,\nMarkov Brains are networks built from individual computational components.\nThese computational components interact with each other, receive inputs from\nsensors, and control motor outputs. The function of the computational\ncomponents, their connections to each other, as well as connections to sensors\nand motors are all subject to evolutionary optimization. Here we describe in\ndetail how a Markov Brain works, what techniques can be used to study them, and\nhow they can be evolved.","url_abs":"http://arxiv.org/abs/1709.05601v1","url_pdf":"http://arxiv.org/pdf/1709.05601v1.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":"markov-brains-a-technical-introduction","repo_url":"https://github.com/nicholasharris/Markov-Brains-Python","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"markov-brains-a-technical-introduction","repo_url":"https://github.com/pnealgit/mnb_js","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}