Comparative Analysis of Reinforcement Learning Algorithms for Bipedal Robot Locomotion
In this research, an optimization methodology was introduced for improving bipedal robot locomotion controlled by reinforcement learning (RL) algorithms. Specifically, the study focused on optimizing the Proximal Policy Optimization (PPO), Advantage Actor-Critic (A2C), Soft Actor-Critic (SAC), and T...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10364844/ |