Selective Asymmetric Recovery: Energy-Driven Semantic Repair from Proto-Inconsistency (Tripwire Note)

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Authors: William Bailey, OpenAI ChatGPT 5.2
Cited by: 2

Abstract

This Tripwire Note introduces a selectively asymmetric, Lyapunov-driven framework for recovering semantic structure from mis-specified definitions and proto-inconsistent identities. Rather than treating incorrect statements as fatal errors, the framework interprets them as energetic constraints that sculpt an irreversible recovery dynamics over a space of semantic interpretations. A Lyapunov-type energy functional penalizes residual inconsistency and excess complexity while enforcing asymmetric descent toward metastable semantic attractors. Convergence is metastable rather than absolute, reflecting the geometry of the induced energy landscape and allowing maximal consistent subsets of proto-identities to be recovered exactly. The construction reframes foundational obstruction and “Monster” regimes as energy phenomena rather than logical failures, and provides diagnostic infrastructure compatible with barrier methods, controlled puncture strategies, and Lyapunov-based analysis. This note is intentionally released as a Tripwire artifact to establish provenance and clarify scope prior to integration into a broader framework.

Fields of Study & Subjects

Embodied and Extended Cognition Philosophy and History of Science Origins and Evolution of Life

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
24 January 2026
Language
EN
Document type
Preprint