Resolving the P vs NP Problem with AI-Driven Computational Insights

This paper presents an AI-assisted investigation into the P vs NP problem. By leveraging advanced computational techniques, we examine the fundamental properties of NP-completeness and explore possible resolution strategies. This submission includes the full LaTeX source files, bibliography, and required macros for reproducibility.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-22
DOI
https://doi.org/10.5281/zenodo.14909256
Primary Topic
Cell Adhesion Molecules Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Resolving the P vs NP Problem with AI-Driven Computational Insights

Zenodo (CERN European Organization for Nuclear Research)
Cell Adhesion Molecules Research
article

Resolving the P vs NP Problem with AI-Driven Computational Insights

article en

Abstract

This paper presents an AI-assisted investigation into the P vs NP problem. By leveraging advanced computational techniques, we examine the fundamental properties of NP-completeness and explore possible resolution strategies. This submission includes the full LaTeX source files, bibliography, and required macros for reproducibility.

Zenodo (CERN European Organization for Nuclear Research)
Gender equality
Openalex Percentile: Top 41%
Cell Adhesion Molecules Research
DOIOpen Access PDFOpenAlex
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Resolving the P vs NP Problem with AI-Driven Computational Insights · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS