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Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments

272 upvotes · 3 SEP 2026 · Jie Wu, Zhenru Zhang, Beichen Zhang et al.

This paper develops a method to turn agent trajectories into reusable environments, allowing for more efficient testing and interaction with the agent. Practitioners might care because this approach can help scale agent training and improve performance in various applications.

continual learningagent trajectoriesterminal environmentstask synthesiscode execution history