3 papers
cs.AI2026
PhysMAS: Physics-Grounded Multi-Agent Synthesis of Compositional 4D Gaussians
Jiang Qin, Chunji Lv, Yangguang Wei +6
Efficient, fully automatic, and physically plausible 4D Gaussian synthesis is an important goal for dynamic scene generation. Recent physics-based methods couple 3D Gaussians with…
cs.AI2026
PCSD: Persistent Consistency for Self-Distillation in Agentic Reinforcement Learning
Chunji Lv, Yangguang Wei, Junlin Liu +6
Large language model agents have shown strong potential in complex interactive tasks, yet their reinforcement learning (RL) is often hindered by sparse rewards, as a long multi-tur…
cs.AI2026
Evolutionary Enhanced Multi-Agent Reinforcement Learning for Cooperative Air Combat
Chengwei Li, Junlin Liu, Yang Gao
As modern air combat evolves toward beyond-visual-range (BVR) multi-aircraft cooperative engagements, autonomous decision-making for unmanned combat aerial vehicles (UCAVs) faces s…