eess.SY(2025-05-12)

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支柱一:机器人控制 (Robot Control) (3) 支柱二:RL算法与架构 (RL & Architecture) (1)

🔬 支柱一:机器人控制 (Robot Control) (3 篇)

#题目一句话要点标签🔗
1 Leveraging Reinforcement Learning and Koopman Theory for Enhanced Model Predictive Control Performance 提出基于Koopman理论与深度强化学习的模型预测控制方法以提升性能 MPC model predictive control reinforcement learning
2 Integrated Localization and Path Planning for an Ocean Exploring Team of Autonomous Underwater Vehicles with Consensus Graph Model Predictive Control 提出基于共识图模型预测控制的AUV团队定位与路径规划方法 MPC model predictive control
3 Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics 提出基于有限样本的可达性方法以实现安全控制 MPC model predictive control

🔬 支柱二:RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗
4 Multi-Objective Reinforcement Learning for Energy-Efficient Industrial Control 提出多目标强化学习框架以实现工业控制的能源效率 reinforcement learning

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