Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion-Reference-Cited by-同舟云学术

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Reward-Adaptive Reinforcement Learning: Dynamic Policy Gradient Optimization for Bipedal Locomotion

Published:2023-06-01 Issue:6 Volume:45 Page:7686-7695
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Huang Changxin¹^ORCID,Wang Guangrun²,Zhou Zhibo³,Zhang Ronghui¹^ORCID,Lin Liang³^ORCID

Affiliation:

1. School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China

2. Department of Engineering Science, University of Oxford, Oxford, United Kingdom

3. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

GuangDong Basic and Applied Basic Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10120646/09956746.pdf?arnumber=9956746

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3. Entropy-Weighted Numerical Gradient Optimization Spiking Neural System for Biped Robot Control;International Journal of Neural Systems;2024-04-13

4. Time-Varying Weights in Multi-Reward Architecture for Deep Reinforcement Learning;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-04

5. Reinforcement Learning of Bipedal Walking Using a Simple Reference Motion;Applied Sciences;2024-02-22

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