Eßer, JulianJulianEßerBach, NicolasNicolasBachJestel, ChristianChristianJestelUrbann, OliverOliverUrbannKerner, SörenSörenKerner2024-01-082024-01-082023https://publica.fraunhofer.de/handle/publica/43027610.1109/MRA.2022.3207664Recent 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.enRobotsTask analysisPipelinesTrainingTaxonomyAutomationComputational modelingjournal article