Preprint
Aug 2026
Harness-RL: Black-Box Reinforcement Learning with Action-Args Decoupling for Central-Agent Multi-Agent Harnesses
Harness-RL is introduced, a structured reinforcement learning framework that combines Conflict-Aware Policy Optimization (CAPO) with interface-level black-box trajectory construction and supports both central-only and joint multi-agent training.
Xinke Jiang, Zhixin Zhang, Zhibang Yang et al.
· 0 citations