AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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MirrorCraft is introduced, a paired benchmark for evaluating agents under hidden rule changes in Minecraft and provides a controlled setting for studying how agents use gameplay outcomes when the rules of the current world differ from familiar ones.
This work proposes $O^2-CritiCuRL, a novel curriculum reinforcement learning framework that introduces critical-step awareness through an iterative offline-online paradigm, and employs a progressive step-level reinforcement learning strategy, where truncated chains guide the model to infer missing steps and refine its reasoning.
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