Author

Ya-Sha Wang

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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