Abstract
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.
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CITATION STYLE
Eber, J., Bach, N., Jestel, C., Urbann, O., & Kerner, S. (2023, June 1). Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics [Survey]. IEEE Robotics and Automation Magazine. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/MRA.2022.3207664
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