EnvACE is a novel agentic reinforcement learning approach that replaces costly real or simulated environment interactions with world rehearsal during training. The method enables policies to alternate between generating tool calls and internally simulating environment responses, improving scalability for long-horizon tasks. Researchers Zishan Xu et al