Hierarchical Reinforcement Learning for Swarm Confrontation with High Uncertainty

1 code implementation • 12 Jun 2024 • Qizhen Wu, Kexin Liu, Lei Chen, Jinhu Lü

In swarm robotics, confrontation including the pursuit-evasion game is a key scenario.

Deep Reinforcement Learning Hierarchical Reinforcement Learning +1

Multi-Agent Reinforcement Learning-Based UAV Pathfinding for Obstacle Avoidance in Stochastic Environment

1 code implementation • 25 Oct 2023 • Qizhen Wu, Kexin Liu, Lei Chen, Jinhu Lü

Traditional methods plan feasible paths for multiple agents in the stochastic environment.

Model Predictive Control Multi-agent Reinforcement Learning +2

Model predictive control-based value estimation for efficient reinforcement learning

1 code implementation • 25 Oct 2023 • Qizhen Wu, Kexin Liu, Lei Chen

Reinforcement learning suffers from limitations in real practices primarily due to the number of required interactions with virtual environments.

Model Predictive Control reinforcement-learning +1

Data-driven, multi-moment fluid modeling of Landau damping

no code implementations • 10 Sep 2022 • Wenjie Cheng, Haiyang Fu, Liang Wang, Chuanfei Dong, YaQiu Jin, Mingle Jiang, Jiayu Ma, Yilan Qin, Kexin Liu

The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve fluid closure and reduce the computational cost of multi-scale modeling of global systems.

An Improved Reinforcement Learning Algorithm for Learning to Branch

no code implementations • 17 Jan 2022 • Qingyu Qu, Xijun Li, Yunfan Zhou, Jia Zeng, Mingxuan Yuan, Jie Wang, Jinhu Lv, Kexin Liu, Kun Mao

Similar to offline reinforcement learning, we initially train on the demonstration data to accelerate learning massively.

Combinatorial Optimization Imitation Learning +3