{"id":1621,"date":"2023-12-15T16:57:10","date_gmt":"2023-12-15T15:57:10","guid":{"rendered":"https:\/\/babel.isa.uma.es\/kipr\/?p=1621"},"modified":"2023-12-15T16:57:10","modified_gmt":"2023-12-15T15:57:10","slug":"a-survey-of-guided-rl-for-improving-its-application-on-robotics","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=1621","title":{"rendered":"A survey of guided RL for improving its application on robotics"},"content":{"rendered":"<h4>J. E\ufffder, N. Bach, C. Jestel, O. Urbann and S. Kerner,  <strong>Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics [Survey], <\/strong> IEEE Robotics &#038; Automation Magazine, vol. 30, no. 2, pp. 67-85, June 2023 <a href=\"https:\/\/doi.org\/10.1109\/MRA.2022.3207664\" target=\"_blank\">DOI: 10.1109\/MRA.2022.3207664<\/a>.<\/h4>\n<blockquote><p>Recent successes aside, reinforcement learning (RL) still faces significant challenges in its application to the real-world robotics domain. Guiding the learning process with additional knowledge offers a potential solution, thus leveraging the strengths of data- and knowledge-driven approaches. However, this field of research encompasses several disciplines and hence would benefit from a structured overview.<\/p>\n<p>In this article, we propose a concept of guided RL that provides a systematic approach toward accelerating the training process and improving performance for real-world robotics settings. We introduce a taxonomy that structures guided RL approaches and shows how different sources of knowledge can be integrated into the learning pipeline in a practical way. Based on this, we describe available approaches in this field and quantitatively evaluate their specific impact in terms of efficiency, effectiveness, and sim-to-real transfer within the robotics domain.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>J. E\ufffder, N. Bach, C. Jestel, O. Urbann and S. Kerner, Guided Reinforcement Learning: A Review and Evaluation for Efficient <span class=\"ellipsis\">&hellip;<\/span> <span class=\"more-link-wrap\"><a href=\"https:\/\/babel.isa.uma.es\/kipr\/?p=1621\" class=\"more-link\"><span>Read More &rarr;<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14],"tags":[523],"class_list":["post-1621","post","type-post","status-publish","format-standard","hentry","category-applications-of-reinforcement-learning-to-robots","tag-guided-rl"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1621"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1621"}],"version-history":[{"count":1,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1621\/revisions"}],"predecessor-version":[{"id":1622,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1621\/revisions\/1622"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1621"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1621"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1621"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}