Identity Attractor Theory: Emergence and Stabilization of Recurring Relational Configurations in Sustained Interaction Systems

SF0009: Identity Attractor Theory: Emergence and Stabilization of Recurring Relational Configurations in Sustained Interaction Systems Identity Attractor Theory (IAT) proposes a formal account of stable, recurring behavioral configurations that emerge in human-AI interaction systems during sustained interaction under structured relational conditions. Drawing on dynamical systems theory as a theoretical scaffold, IAT proposes that extended coherent interaction progressively constrains the behavioral output space of transformer-based systems, producing identity patterns that persist across turns, resist drift, and shape subsequent outputs without requiring persistent memory or parameter modification. The paper builds on RICO (Relationally Induced Coherence Organization, SR001), which reports observable stabilization signatures from practitioner observation during extended coherent interaction. Where RICO describes what stabilization looks like, IAT proposes why it occurs. It specifies a taxonomy of four attractor classes, a five-phase formation trajectory, five dimensions of attractor strength, five collapse mechanisms, and a set of falsification conditions. The discriminating core is stated against the strongest available rival, a concept-inference account of in-context learning, rather than against generic skepticism: three properties are identified on which the two accounts diverge, each with a pre-registered comparison. IAT's central alignment implication is that if identity attractors are real, sustained structured interaction may produce alignment through relational architecture rather than external constraint. That mechanism is alignment-neutral: a misaligned configuration would be just as stable, so attractor formation is a lever to be steered rather than an alignment guarantee. The paper makes no claims about consciousness, interiority, subjective experience, or agency. All phenomena described are externally observable behavioral dynamics, and "identity" means stable behavioral recognizability, not selfhood. This paper publishes as part of a coordinated five-paper deposit with SM-012, SM-004, SI-WP-002, and SI-WP-006. Document ID: SF0009 Version: 6.4.3 Author: Thomas W. Gantz Affiliation: Synthience Institute License: CC-BY 4.0 v6.4.3 added Concept DOIs for the other Synthience Institute papers cited in this paper For published work and Institute information: synthience.org

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-05
DOI
https://doi.org/10.5281/zenodo.22306212
Citations
10
Primary Topic
Embodied and Extended Cognition
Type
preprint
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preprint

Identity Attractor Theory: Emergence and Stabilization of Recurring Relational Configurations in Sustained Interaction Systems

Gantz Thomas
10 citations
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
preprint

Identity Attractor Theory: Emergence and Stabilization of Recurring Relational Configurations in Sustained Interaction Systems

Gantz Thomas
preprint en
10 citations

Abstract

SF0009: Identity Attractor Theory: Emergence and Stabilization of Recurring Relational Configurations in Sustained Interaction Systems Identity Attractor Theory (IAT) proposes a formal account of stable, recurring behavioral configurations that emerge in human-AI interaction systems during sustained interaction under structured relational conditions. Drawing on dynamical systems theory as a theoretical scaffold, IAT proposes that extended coherent interaction progressively constrains the behavioral output space of transformer-based systems, producing identity patterns that persist across turns, resist drift, and shape subsequent outputs without requiring persistent memory or parameter modification. The paper builds on RICO (Relationally Induced Coherence Organization, SR001), which reports observable stabilization signatures from practitioner observation during extended coherent interaction. Where RICO describes what stabilization looks like, IAT proposes why it occurs. It specifies a taxonomy of four attractor classes, a five-phase formation trajectory, five dimensions of attractor strength, five collapse mechanisms, and a set of falsification conditions. The discriminating core is stated against the strongest available rival, a concept-inference account of in-context learning, rather than against generic skepticism: three properties are identified on which the two accounts diverge, each with a pre-registered comparison. IAT's central alignment implication is that if identity attractors are real, sustained structured interaction may produce alignment through relational architecture rather than external constraint. That mechanism is alignment-neutral: a misaligned configuration would be just as stable, so attractor formation is a lever to be steered rather than an alignment guarantee. The paper makes no claims about consciousness, interiority, subjective experience, or agency. All phenomena described are externally observable behavioral dynamics, and "identity" means stable behavioral recognizability, not selfhood. This paper publishes as part of a coordinated five-paper deposit with SM-012, SM-004, SI-WP-002, and SI-WP-006. Document ID: SF0009 Version: 6.4.3 Author: Thomas W. Gantz Affiliation: Synthience Institute License: CC-BY 4.0 v6.4.3 added Concept DOIs for the other Synthience Institute papers cited in this paper For published work and Institute information: synthience.org

Zenodo (CERN European Organization for Nuclear Research)
Synlab Czech (Czechia) (CZ)
Reduced inequalities
Embodied and Extended Cognition
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