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Language-Based Agent Control
Papers46
The work addresses language-based agent control, exploring how natural language directives can govern behavioral planning and policy execution in autonomous systems. By substituting or augmenting rigid reward engineering with linguistic interfaces, such approaches aim to achieve more adaptable task grounding. With limited documentation currently exposed in the submission index, the concrete benchmarks and empirical rigor remain to be verified upon full paper release.
Why it's worth reading
As natural language increasingly acts as an operational control plane for autonomous agents, monitoring emerging formulations helps track shifts away from classical reward engineering.
Tags
AI AgentLanguage ControlRoboticsReinforcement LearningarXiv