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Can Agents Infer Environment from Interaction? Evidence from Agentic Automata Learning
We propose agentic automata learning to evaluate the extent to which tool-calling LLM agents can uncover hidden environments through interaction, a capability increasingly required in agentic tasks (e.g., reproducing an executable without access to its source code by interacting with it). In our set
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