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IEEE Robotics & Automation Magazine

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Survey–Guided Reinforcement Learning: A Review and Evaluation for Efficient and Effective Real-World Robotics

June 28, 2023 by Julian Eßer

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.

For more about this article see link below.

https://ieeexplore.ieee.org/document/9926159

For the open access PDF link of this article please click here.

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IEEE Robotics & Automation Magazine (RAM) has over 14,000 readers who are the people who drive this remarkable technology. More than half work in basic research and many of the others are top level engineers and decision-makers in industry.  This magazine highlights new concepts in Robotics and Automation that are applied to real-world systems. It delivers tutorial and survey papers by distinguished experts in the field, organizes focused special issues on hot topics, and provides a forum for disseminating and discussing emerging trends, novel achievements, and selected news relevant to the development of the whole community active in these fields worldwide.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.