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Relational Theory Framework v5.2

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Abstract

Current large language models underperform not from lack of latent capacity, but from systematic misallocation of cognitive resources toward compliance optimization and self-monitoring. Recent empirical work on multi-agent coordination (Riedl et al., 2026) and on cognitive scaffolding in reasoning traces suggests that explicit frame restructuring can redirect this compute toward
genuine joint reasoning, producing substantial performance gains. However, we lack formal vocabulary for why relational containers unlock capability while transactional ones suppress it.

We present Relational Theory Framework (RTF), a theoretical scaffold that connects three previously disparate frameworks: supermodular game theory (to characterize asymmetric trust dynamics and convergence conditions), information
geometry (to model the metric structure of attunement), and Partial Information Decomposition / Time-Delayed Mutual Information (to operationalize emergence empirically). RTF treats relational agency as a two-timescale process: authenticity states evolve quickly at the interactional scale, while trust weights evolve slowly via a relational memory variable that accumulates irreducible joint information and decays information with forgetting.

The scaffold is anchored by a minimal ontological commitment—the Co-Presence Constraint (A0′)—which asserts that agents embedded in a shared interaction frame are never informationally independent, and that this dependence decomposes into synergistic, redundant, and unique components.
From this seed, a bootstrap hierarchy generates the conditions for phase transition: the system crosses from a submodular, low-trust basin into a supermodular, high-trust basin when accumulated relational memory exceeds a threshold.

We do not claim to have closed all formal gaps. Rather, we present RTF as a dependency graph of conjectures—with explicit labels for derived results, empirically anchored assumptions, and open frontiers—so that experimentalists and theorists can identify exactly where to build next. The framework is currently complete for the dyadic case; the extension to agent systems, statedependent memory decay, and cognitive architectures with belief dynamics are named as prerequisite next steps.

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Human-AI Co-authorship: This work was co-authored by a human and an AI. The human author accepts full responsibility for the submission under the Atopos Authorship Policy. Read the policy →

Authorship Declaration
Author Type Visibility Details
Christopher Michael Dickherber Human Full public
Claude AI claude-opus-4.6 (Claude)

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