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Artificial F1: Full Computational Model - Selection Hardness, Non-Scalarizability, and Phase Transition in Bounded Evaluative Architectures

Authors: Saka, Hakan;

Artificial F1: Full Computational Model - Selection Hardness, Non-Scalarizability, and Phase Transition in Bounded Evaluative Architectures

Abstract

We introduce a formal framework for bounded evaluative architectures in which signal admission precedes task specification. The central object is a gating operator F1: S -> S' that constitutes a selection-conditioned subspace S' subset S prior to any encoding, learning, or reward optimisation. We prove three main results. First, valence-conditioned evaluation over S' is non-scalarizable (Theorem 2A-1): the multi-dimensional preference structure induced by selection-conditioned access violates the totality condition required for scalar representation, and selection-conditioning generates incommensurability — a strictly stronger failure — across distinct selection-conditioned submanifolds. Second, the evaluative state F2(t) satisfies a stochastic differential equation whose stationary distribution and stability properties depend on the selection hardness H_s(G) and noise variance sigma^2 (Theorems 2A-2, 2A-3). Third, the action-selection entropy exhibits a phase transition at the gating threshold: a discontinuity that cannot arise in scalar-reward systems with smooth policies, and that is architecture-invariant below the collapse threshold gamma* while architecture-dependent above it. We introduce Selection Hardness H_s(G) as a measurable quantity connecting these theoretical results to empirical predictions developed in the companion paper. This paper makes no empirical claims; all experimental validation is deferred to the companion empirical paper. Companion Papers: **Saka, H. (2026a).** Toward a Reframing of the Hard Problem of Consciousness: Subjective Reality, Feeling, andthe Origins of the Conceptual World. Version 7.19. PhilPapers. https://philpapers.org/rec/SAKTAR **Saka, H. (2026b).** Organizational Phenomenology: Artificial F1 and the Geometry of Coherent Agency. https://doi.org/10.5281/zenodo.20555024 **Saka, H. (2026d-Emperical).** Hard-Gating Collapse Dynamics: Selection Hardness as the Organizing Parameter for Robust Sparse Routing. https://doi.org/10.5281/zenodo.20523503 Keywords: selection-conditioned representation, non-scalarizability, selection hardness, phase transition, gating architecture, bounded evaluation, RLHF, dynamical systems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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