{"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/learning-curriculum-policies-for","title":"Learning Curriculum Policies for Reinforcement Learning","arxiv_id":"1812.00285","date":"2018-12-01","proceeding":null,"authors":["Sanmit Narvekar","Peter Stone"],"abstract":"Curriculum learning in reinforcement learning is a training methodology that\nseeks to speed up learning of a difficult target task, by first training on a\nseries of simpler tasks and transferring the knowledge acquired to the target\ntask. Automatically choosing a sequence of such tasks (i.e. a curriculum) is an\nopen problem that has been the subject of much recent work in this area. In\nthis paper, we build upon a recent method for curriculum design, which\nformulates the curriculum sequencing problem as a Markov Decision Process. We\nextend this model to handle multiple transfer learning algorithms, and show for\nthe first time that a curriculum policy over this MDP can be learned from\nexperience. We explore various representations that make this possible, and\nevaluate our approach by learning curriculum policies for multiple agents in\ntwo different domains. The results show that our method produces curricula that\ncan train agents to perform on a target task as fast or faster than existing\nmethods.","url_abs":"http://arxiv.org/abs/1812.00285v1","url_pdf":"http://arxiv.org/pdf/1812.00285v1.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":"learning-curriculum-policies-for","repo_url":"https://github.com/holman57/ML-Education","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.00285","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}