Jinghao Lin

Asynchronous RL training on long-horizon tasks achieves superior performance by leveraging Muon and a novel single-rollout recipe that avoids waiting for complete trajectories.

Standardizing terminal-outcome advantages can significantly boost online learning efficiency in asynchronous reinforcement learning scenarios.