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cs.AI2026
ACPO: Agent-Chained Policy Optimization for Multi-Agent Reinforcement Learning
Daiki E. Matsunaga, Junho Na, Tri Wahyu Guntara +4
Cooperative tasks in Multi-Agent Reinforcement Learning (MARL) require agents to collectively maximize a shared return. Under the Centralized Training with Decentralized Execution…
cs.LG2026
Blocked Gibbs meets Diffusion Transformers: Unsupervised Learning for Constraint Optimization
Yudong W. Xu, Wenhao Li, Xiaoyu Wang +2
Diffusion models have shown promise in learning to solve constraint optimization problems. However, they are mostly restricted to problems with binary variables and rely on graph n…