{"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/mirror-descent-search-and-its-acceleration","title":"Mirror Descent Search and its Acceleration","arxiv_id":"1709.02535","date":"2017-09-08","proceeding":null,"authors":["Megumi Miyashita","Shiro Yano","Toshiyuki Kondo"],"abstract":"In recent years, attention has been focused on the relationship between\nblack-box optimiza- tion problem and reinforcement learning problem. In this\nresearch, we propose the Mirror Descent Search (MDS) algorithm which is\napplicable both for black box optimization prob- lems and reinforcement\nlearning problems. Our method is based on the mirror descent method, which is a\ngeneral optimization algorithm. The contribution of this research is roughly\ntwofold. We propose two essential algorithms, called MDS and Accelerated Mirror\nDescent Search (AMDS), and two more approximate algorithms: Gaussian Mirror\nDescent Search (G-MDS) and Gaussian Accelerated Mirror Descent Search (G-AMDS).\nThis re- search shows that the advanced methods developed in the context of the\nmirror descent research can be applied to reinforcement learning problem. We\nalso clarify the relationship between an existing reinforcement learning\nalgorithm and our method. With two evaluation experiments, we show our proposed\nalgorithms converge faster than some state-of-the-art methods.","url_abs":"http://arxiv.org/abs/1709.02535v2","url_pdf":"http://arxiv.org/pdf/1709.02535v2.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":"mirror-descent-search-and-its-acceleration","repo_url":"https://github.com/mmilk1231/MirrorDescentSearch","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"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":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}