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Keywords: deep reinforcement learning
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Proceedings Papers

Proc. ASME. IDETC-CIE2023, Volume 1: 25th International Conference on Advanced Vehicle Technologies (AVT), V001T01A015, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-113683
... such a deep reinforcement learning-based optimal vehicle cruise control. The most commonly used algorithm, deep deterministic policy gradient (DDPG), overestimates Q-functions that can lead to sub-optimal agent policy. We proposed the twin-delayed DDPG (TD3) algorithm, the extension of the DDPG algorithm. We...
Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A072, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89829
... in Engineering Conference IDETC-CIE2022 August 14-17, 2022, St. Louis, Missouri DETC2022-89829 DISCOVERY OF CUSTOMIZED DISPATCHING RULE FOR SINGLE-MACHINE PRODUCTION SCHEDULING USING DEEP REINFORCEMENT LEARNING Ping Chong Chua, Seung Ki Moon1 School of Mechanical and Aerospace Engineering Nanyang Technological...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3B: 47th Design Automation Conference (DAC), V03BT03A036, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-67225
... reinforcement learning deep Q-network Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August 17-19, 2021, Virtual, Online DETC2021-67225 DEEP REINFORCEMENT LEARNING ENHANCED CONVOLUTIONAL NERUAL...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 5A: 43rd Mechanisms and Robotics Conference, V05AT07A048, August 18–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: DETC2019-97536
... Abstract Obstacle avoidance is one of the core problems in the field of mobile robot autonomous navigation. This paper aims to solve the obstacle avoidance problem using Deep Reinforcement Learning. In previous work, various mathematical models have been developed to plan collision-free paths...
Topics: Mobile robots