1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.RO2025
Symmetry-Guided Multi-Agent Inverse Reinforcement Learning
Yongkai Tian, Yirong Qi, Xin Yu +2
In robotic systems, the performance of reinforcement learning depends on the rationality of predefined reward functions. However, manually designed reward functions often lead to p…
cs.AI2025
Embedded Mean Field Reinforcement Learning for Perimeter-defense Game
Li Wang, Xin Yu, Xuxin Lv +2
With the rapid advancement of unmanned aerial vehicles (UAVs) and missile technologies, perimeter-defense game between attackers and defenders for the protection of critical region…
cs.AI2024★ 1 cited
Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Tasks
Pu Feng, Junkang Liang, Size Wang +6
In multi-agent reinforcement learning (MARL), the Centralized Training with Decentralized Execution (CTDE) framework is pivotal but struggles due to a gap: global state guidance in…