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This paper from Fudan University defines autonomous agents as systems that maintain task goals and viability conditions within explicit authority boundaries, proposing a one-boundary, four-loop framework (Operational, Viability, Reflexive, and Learning loops) and validating it through five paired simulation experiments on permission constraints, environment response, health maintenance, capability re-estimation, and cross-task learning.
A LessWrong research post exploring how self-modeling interventions can modulate emergent misalignment in language models, examining whether models' representations of themselves influence their generalization toward misaligned behavior.
The article proposes a long-term experiment to preserve the developmental continuity of an embodied AI agent over decades to study consciousness and individuality, comparing it with newly initialized agents.