Formed, Not Stored: Testing Relational Identity Formation in Long-Horizon Language Agents

Persistent agents are often treated as continuous when they retain memory or persona files. This paper argues that storage-based continuity is insufficient: personalization concerns how an agent adapts toward a user, whereas functional individuation concerns how interaction organizes the agent's own actions, commitments, and dispositions. We propose relational identity formation, in which repeated re-identification by a specific counterpart helps make prior agent conduct causally relevant to later decisions. Our contribution is not another memory architecture but the controlled isolation of counterpart-specific re-identification as a candidate causal mechanism for agent-side functional individuation. We specify an architecture coupling autobiographical memory, an updatable self-model, counterpart modeling, relational memory, commitment provenance, and safeguards against sycophancy. A longitudinal protocol compares a persistent re-identifying counterpart (R+), a persistent non-reidentifying counterpart (R-), content-matched solitary logs, diffuse counterparts, and a pre-authored persona. Primary outcomes are commitment ownership and perturbation resistance. Scaffold withdrawal, counterpart transfer, oracle retrieval, and component ablations distinguish formed organization from prompting, recall, familiarity, and compliance. The hypothesis is weakened if R+ does not outperform content- and familiarity-matched controls or if differences are explained by retrieval, personalization, or sycophancy. The framework makes no claim about phenomenal consciousness, personhood, or moral status. It treats persistent agent identity as a falsifiable property of coupled agent-counterpart trajectories rather than isolated model state.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-30
DOI
https://doi.org/10.5281/zenodo.21052695
Primary Topic
Social Robot Interaction and HRI
Type
preprint
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preprint

Formed, Not Stored: Testing Relational Identity Formation in Long-Horizon Language Agents

Rafael de Menezes Ehlers
Zenodo (CERN European Organization for Nuclear Research)
Social Robot Interaction and HRI
preprint

Formed, Not Stored: Testing Relational Identity Formation in Long-Horizon Language Agents

Rafael de Menezes Ehlers
preprint en

Abstract

Persistent agents are often treated as continuous when they retain memory or persona files. This paper argues that storage-based continuity is insufficient: personalization concerns how an agent adapts toward a user, whereas functional individuation concerns how interaction organizes the agent's own actions, commitments, and dispositions. We propose relational identity formation, in which repeated re-identification by a specific counterpart helps make prior agent conduct causally relevant to later decisions. Our contribution is not another memory architecture but the controlled isolation of counterpart-specific re-identification as a candidate causal mechanism for agent-side functional individuation. We specify an architecture coupling autobiographical memory, an updatable self-model, counterpart modeling, relational memory, commitment provenance, and safeguards against sycophancy. A longitudinal protocol compares a persistent re-identifying counterpart (R+), a persistent non-reidentifying counterpart (R-), content-matched solitary logs, diffuse counterparts, and a pre-authored persona. Primary outcomes are commitment ownership and perturbation resistance. Scaffold withdrawal, counterpart transfer, oracle retrieval, and component ablations distinguish formed organization from prompting, recall, familiarity, and compliance. The hypothesis is weakened if R+ does not outperform content- and familiarity-matched controls or if differences are explained by retrieval, personalization, or sycophancy. The framework makes no claim about phenomenal consciousness, personhood, or moral status. It treats persistent agent identity as a falsifiable property of coupled agent-counterpart trajectories rather than isolated model state.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Social Robot Interaction and HRI
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