{"type":"journal_article","language":[{"iso":"eng"}],"date_created":"2022-01-28T14:11:08Z","status":"public","author":[{"last_name":"Schenke","id":"52638","full_name":"Schenke, Maximilian","first_name":"Maximilian","orcid":"0000-0001-5427-9527"},{"full_name":"Wallscheid, Oliver","id":"11291","last_name":"Wallscheid","orcid":"https://orcid.org/0000-0001-9362-8777","first_name":"Oliver"}],"_id":"29662","title":"Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning","date_updated":"2022-02-25T20:31:17Z","citation":{"apa":"Schenke, M., & Wallscheid, O. (2021). Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning. ArXiv Preprint ArXiv:2105.08990.","short":"M. Schenke, O. Wallscheid, ArXiv Preprint ArXiv:2105.08990 (2021).","chicago":"Schenke, Maximilian, and Oliver Wallscheid. “Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning.” ArXiv Preprint ArXiv:2105.08990, 2021.","bibtex":"@article{Schenke_Wallscheid_2021, title={Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning}, journal={arXiv preprint arXiv:2105.08990}, author={Schenke, Maximilian and Wallscheid, Oliver}, year={2021} }","ieee":"M. Schenke and O. Wallscheid, “Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning,” arXiv preprint arXiv:2105.08990, 2021.","ama":"Schenke M, Wallscheid O. Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning. arXiv preprint arXiv:210508990. Published online 2021.","mla":"Schenke, Maximilian, and Oliver Wallscheid. “Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning.” ArXiv Preprint ArXiv:2105.08990, 2021."},"user_id":"11291","publication":"arXiv preprint arXiv:2105.08990","department":[{"_id":"52"},{"_id":"57"}],"year":"2021"}