A Mathematical Conflict Framework for Contextual Data Modulation

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteur principal: Kartal, Hakan Emre
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866910282192781312
author Kartal, Hakan Emre
author_facet Kartal, Hakan Emre
contents In this study, a generalized operator-based mathematical conflict framework is presented to explicitly represent structural discrepancies between raw data and contextual data. The proposed structure treats conflict as a local, directional, and context-sensitive quantity, integrating components such as weighting, scale behavior, and output mapping under a unified abstract operator. Without being reduced to a specific learning algorithm or optimization method, the framework is defined as a general structure adaptable to different classes of problems. While existing approaches typically treat conflict merely as an implicit side effect embedded within the optimization process, the proposed framework considers conflict as an independent, operator-based, and component-level mathematical object.
format Preprint
id arxiv_https___arxiv_org_abs_2606_02381
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Mathematical Conflict Framework for Contextual Data Modulation
Kartal, Hakan Emre
Artificial Intelligence
Machine Learning
Dynamical Systems
In this study, a generalized operator-based mathematical conflict framework is presented to explicitly represent structural discrepancies between raw data and contextual data. The proposed structure treats conflict as a local, directional, and context-sensitive quantity, integrating components such as weighting, scale behavior, and output mapping under a unified abstract operator. Without being reduced to a specific learning algorithm or optimization method, the framework is defined as a general structure adaptable to different classes of problems. While existing approaches typically treat conflict merely as an implicit side effect embedded within the optimization process, the proposed framework considers conflict as an independent, operator-based, and component-level mathematical object.
title A Mathematical Conflict Framework for Contextual Data Modulation
topic Artificial Intelligence
Machine Learning
Dynamical Systems
url https://arxiv.org/abs/2606.02381