{"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/reservoir-computing-using-cellular-automata","title":"Reservoir Computing using Cellular Automata","arxiv_id":"1410.0162","date":"2014-10-01","proceeding":null,"authors":["Ozgur Yilmaz"],"abstract":"We introduce a novel framework of reservoir computing. Cellular automaton is\nused as the reservoir of dynamical systems. Input is randomly projected onto\nthe initial conditions of automaton cells and nonlinear computation is\nperformed on the input via application of a rule in the automaton for a period\nof time. The evolution of the automaton creates a space-time volume of the\nautomaton state space, and it is used as the reservoir. The proposed framework\nis capable of long short-term memory and it requires orders of magnitude less\ncomputation compared to Echo State Networks. Also, for additive cellular\nautomaton rules, reservoir features can be combined using Boolean operations,\nwhich provides a direct way for concept building and symbolic processing, and\nit is much more efficient compared to state-of-the-art approaches.","url_abs":"http://arxiv.org/abs/1410.0162v1","url_pdf":"http://arxiv.org/pdf/1410.0162v1.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":"reservoir-computing-using-cellular-automata","repo_url":"https://github.com/sciml/reservoircomputing.jl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"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}