Deep Reinforcement Learning With Optimized Reward Functions for Robotic Trajectory Planning
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2932257
Abstract: To improve the efficiency of deep reinforcement learning (DRL)-based methods for robotic trajectory planning in the unstructured working environment with obstacles. Different from the traditional sparse reward function, this paper presents two brand-new dense reward… read more here.
Keywords: reward functions; reinforcement learning; trajectory; deep reinforcement ... See more keywords
Designing Reward Functions Using Active Preference Learning for Reinforcement Learning in Autonomous Driving Navigation
Sign Up to like & getrecommendations! Published in 2024 at "Applied Sciences"
DOI: 10.3390/app14114845
Abstract: This study presents a method based on active preference learning to overcome the challenges of designing reward functions for autonomous navigation. Results obtained from training with artificially designed reward functions may not accurately reflect human… read more here.
Keywords: reward functions; navigation; preference learning; active preference ... See more keywords