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ISO-690 (author-date, English)

DREWING, Nadine, AHMADI, Arjang, XIONG, Xiaofeng und AHMAD SHARBAFI, Maziar, 2024. Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance : Does AI Always Win?. Basel: MDPI.

Elsevier - Harvard (with titles)

Drewing, N., Ahmadi, A., Xiong, X., Ahmad Sharbafi, M., 2024. Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance : Does AI Always Win?, Biomimetics. MDPI, Basel. https://doi.org/10.26083/tuprints-00028848

American Psychological Association 7th edition

Drewing, N., Ahmadi, A., Xiong, X., & Ahmad Sharbafi, M. (ca. 2024). Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance : Does AI Always Win? [Cd]. In Biomimetics. MDPI. https://doi.org/10.26083/tuprints-00028848

Springer - Basic (author-date)

Drewing N, Ahmadi A, Xiong X, Ahmad Sharbafi M (2024) Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance : Does AI Always Win?. MDPI, Basel

Juristische Zitierweise (Stüber) (Deutsch)

Drewing, Nadine/ Ahmadi, Arjang/ Xiong, Xiaofeng/ Ahmad Sharbafi, Maziar, Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance : Does AI Always Win?, Basel 2024.

Achtung: Diese Zitate sind unter Umständen nicht zu 100% korrekt.