{"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/cycle-of-learning-for-autonomous-systems-from","title":"Cycle-of-Learning for Autonomous Systems from Human Interaction","arxiv_id":"1808.09572","date":"2018-08-28","proceeding":null,"authors":["Nicholas R. Waytowich","Vinicius G. Goecks","Vernon J. Lawhern"],"abstract":"We discuss different types of human-robot interaction paradigms in the\ncontext of training end-to-end reinforcement learning algorithms. We provide a\ntaxonomy to categorize the types of human interaction and present our\nCycle-of-Learning framework for autonomous systems that combines different\nhuman-interaction modalities with reinforcement learning. Two key concepts\nprovided by our Cycle-of-Learning framework are how it handles the integration\nof the different human-interaction modalities (demonstration, intervention, and\nevaluation) and how to define the switching criteria between them.","url_abs":"http://arxiv.org/abs/1808.09572v2","url_pdf":"http://arxiv.org/pdf/1808.09572v2.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":"cycle-of-learning-for-autonomous-systems-from","repo_url":"https://github.com/viniciusguigo/complete_col","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1808.09572","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}