{"id":32819,"date":"2026-01-21T17:02:42","date_gmt":"2026-01-21T17:02:42","guid":{"rendered":"https:\/\/lamarr-institute.org\/publication\/guided-reinforcement-learning-a-review-and-evaluation-for-efficient-and-effective-real-world-robotics-survey\/"},"modified":"2026-09-17T11:26:26","modified_gmt":"2026-09-17T11:26:26","slug":"guided-reinforcement-learning-a-review-and-evaluation-for-efficient-and-effective-real-world-robotics-survey","status":"publish","type":"publication","link":"https:\/\/lamarr-institute.org\/de\/publication\/guided-reinforcement-learning-a-review-and-evaluation-for-efficient-and-effective-real-world-robotics-survey\/","title":{"rendered":"Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics [Survey]"},"content":{"rendered":"<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>\n","protected":false},"excerpt":{"rendered":"<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. In this article, we propose a concept of guided RL that provides a systematic approach toward [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"publication-type":[30],"class_list":["post-32819","publication","type-publication","status-publish","hentry","publication-type-article"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32819","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/types\/publication"}],"author":[{"embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/users\/14"}],"version-history":[{"count":0,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32819\/revisions"}],"wp:attachment":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/media?parent=32819"}],"wp:term":[{"taxonomy":"publication-type","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-type?post=32819"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}