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arXiv · 2608.06968

Same physical state, different collective dynamics: state encodings select synchronization outcomes in language-model agents

Takahiro Ezaki·Naoto Imura·Katsuhiro Nishinari
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Abstract

Language-model agents act on state encodings of their environment, yet these are treated as interchangeable interfaces. Using pretrained language models, we designed a circular-synchronization experiment applying a state-encoding intervention while holding the physical system fixed: each agent sees only a summary of its neighbours' relative phases and chooses to advance, stay or retard. Encoding that state as low-order circular moments rather than as a histogram selected different collective outcomes. In GPT the moment encoding synchronized the population in 6/6 seeds and the histogram encodings in 0/6; the effect replicated in Claude but reversed direction. Replaying identical fields shifted each agent's advance/stay/retard probabilities far beyond within-encoding repeat variation, in GPT, Claude and Gemini; in GPT, presentation alone shifted the operator with the moment values fixed. State encodings therefore form part of a model-dependent effective interaction law, not a neutral interface.

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Takahiro Ezaki, Naoto Imura, Katsuhiro Nishinari. 2026-08-07. Same physical state, different collective dynamics: state encodings select synchronization outcomes in language-model agents. https://arxiv.org/abs/2608.06968

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