In cooperative Multi-Agent Reinforcement Learning (MARL), agents are often trained under concurrent participation, while in many tasks some agents act earlier and leave task-relevant information that becomes useful to agents participating later. We study this setting as staggered participation (SP), which introduces a...
Decoupled Credit Self-Distillation is introduced, which theoretically decouples credit direction and magnitude into two reliable signals and uses them to calibrate privileged teacher supervision, enabling step-to-token credit assignment for policy optimization.
Yu-Gu Li, Ze-Hong Cao, Pei-Zhen Li et al.· 0 citations
This paper proposes a top-down framework for synthesizing hierarchical 3D scene graphs, including a room layer -- describing the floor plan and traversability -- and an object layer modeling object layouts within each room, and proposes a novel mixed-domain graph diffusion model jointly predicting room categories, floo...
Siyi Hu, Jared Strader, Hyungtae Lim et al.· arXiv.org· 0 citations
This work proposes Reverse-Turn Policy Optimization (RTPO), which organizes multi-turn rollouts as sparse reverse trees and performs turn-level policy updates in temporal reverse order, aligning each decision with its downstream continuation.
Yu-Gu Li, Ze-Hong Cao, Jiang-Lin Qiao et al.· 1 citation
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