3 citations · 5 across the 15 of their papers we have counts for
5 papers · 1 filter
ERFSL: An Efficient Reward Function Searcher via Language Models for Custom-Environment Multi-Objective Optimization (Student Abstract)
Guanwen Xie, Jingzehua Xu, Yiyuan Yang +2
We propose ERFSL, an efficient reward function searcher using large language models (LLMs) for custom-environment, multi-objective learning-based methods (LB). ERFSL generates rewa…
AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)
Yimian Ding, Jingzehua Xu, Yiyuan Yang +3
Ocean exploration places high demands on autonomous underwater vehicles, especially when there's observation delay. We propose age of information optimized Markov decision process…
When Motion Learns to Listen: Diffusion-Prior Lyapunov Actor-Critic Framework with LLM Guidance for Stable and Robust AUV Control in Underwater Tasks
Jingzehua Xu, Weiyi Liu, Weihang Zhang +4
Autonomous Underwater Vehicles (AUVs) are indispensable for marine exploration; yet, their control is hindered by nonlinear hydrodynamics, time-varying disturbances, and localizati…
Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks
Yimian Ding, Jingzehua Xu, Guanwen Xie +2
This study presents a novel environment-aware reinforcement learning (RL) framework designed to augment the operational capabilities of autonomous underwater vehicles (AUVs) in und…
Enhancing Information Freshness: An AoI Optimized Markov Decision Process
Jingzehua Xu, Yimian Ding, Yiyuan Yang +2
Ocean exploration utilizing autonomous underwater vehicles (AUVs) via reinforcement learning (RL) has emerged as a significant research focus. However, underwater tasks have mostly…