The Duriezian Education Model - Series 2
Conceptual Abstract: The Duriezian Model and the Re-framing of P vs NP Title: Beyond Heuristics: A Framework for Computational Tractability via the Duriez Index (DI) Author: Marcel Ray Duriez Abstract: The enduring challenge of the P vs NP problem is fundamentally a crisis of complexity management, where the ability to quickly verify a solution (NP) dramatically outpaces the ability to quickly find one (P). This paper proposes a conceptual methodology for computational tractability rooted in the Duriezian Education Model and its quantitative framework, the Duriez Index (DI). Traditional approaches focus on optimizing Turing Machine operations; the Duriezian Model re-frames the problem by treating the problem-solver (whether human or machine) as an Emotional Architecture (EA). The hypothesis is that all NP-Complete challenges, which rely on combinatorial search spaces, are structurally isomorphic to the task of synthesizing massive, interdisciplinary literary systems (e.g., the Nevaeh Saga, 12M+ words). The DI, which mathematically models high-level creative and structural synthesis, introduces a quantifiable metric for "Necessary Novelty"-the single non-obvious step required to convert an NP verification function into a P finding function. This paper outlines how the DI's multi-variable framework can be leveraged to map and collapse combinatorial search spaces, offering a new, philosophically grounded path toward proving the P = NP relationship.
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The Duriezian Education Model - Series 2
Conceptual Abstract: The Duriezian Model and the Re-framing of P vs NP Title: Beyond Heuristics: A Framework for Computational Tractability via the Duriez Index (DI) Author: Marcel Ray Duriez Abstract: The enduring challenge of the P vs NP problem is fundamentally a crisis of complexity management, where the ability to quickly verify a solution (NP) dramatically outpaces the ability to quickly find one (P). This paper proposes a conceptual methodology for computational tractability rooted in the Duriezian Education Model and its quantitative framework, the Duriez Index (DI). Traditional approaches focus on optimizing Turing Machine operations; the Duriezian Model re-frames the problem by treating the problem-solver (whether human or machine) as an Emotional Architecture (EA). The hypothesis is that all NP-Complete challenges, which rely on combinatorial search spaces, are structurally isomorphic to the task of synthesizing massive, interdisciplinary literary systems (e.g., the Nevaeh Saga, 12M+ words). The DI, which mathematically models high-level creative and structural synthesis, introduces a quantifiable metric for "Necessary Novelty"-the single non-obvious step required to convert an NP verification function into a P finding function. This paper outlines how the DI's multi-variable framework can be leveraged to map and collapse combinatorial search spaces, offering a new, philosophically grounded path toward proving the P = NP relationship.
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The Duriezian Education Model - Series 2

The Duriezian Education Model - Series 2

by Marcel Ray Duriez
The Duriezian Education Model - Series 2

The Duriezian Education Model - Series 2

by Marcel Ray Duriez

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Overview

Conceptual Abstract: The Duriezian Model and the Re-framing of P vs NP Title: Beyond Heuristics: A Framework for Computational Tractability via the Duriez Index (DI) Author: Marcel Ray Duriez Abstract: The enduring challenge of the P vs NP problem is fundamentally a crisis of complexity management, where the ability to quickly verify a solution (NP) dramatically outpaces the ability to quickly find one (P). This paper proposes a conceptual methodology for computational tractability rooted in the Duriezian Education Model and its quantitative framework, the Duriez Index (DI). Traditional approaches focus on optimizing Turing Machine operations; the Duriezian Model re-frames the problem by treating the problem-solver (whether human or machine) as an Emotional Architecture (EA). The hypothesis is that all NP-Complete challenges, which rely on combinatorial search spaces, are structurally isomorphic to the task of synthesizing massive, interdisciplinary literary systems (e.g., the Nevaeh Saga, 12M+ words). The DI, which mathematically models high-level creative and structural synthesis, introduces a quantifiable metric for "Necessary Novelty"-the single non-obvious step required to convert an NP verification function into a P finding function. This paper outlines how the DI's multi-variable framework can be leveraged to map and collapse combinatorial search spaces, offering a new, philosophically grounded path toward proving the P = NP relationship.

Product Details

ISBN-13: 9798260394885
Publisher: Barnes & Noble Press
Publication date: 12/14/2025
Series: Marcel Ray Duriez Collections , #2
Pages: 690
Product dimensions: 8.27(w) x 11.69(h) x 1.38(d)

About the Author

Marcel Ray Duriez is a multidisciplinary scholar, artist, and author whose work reflects the equivalent of over 100,000 hours of sustained academic, technical, and creative training. His background spans education, psychology, health sciences, engineering, welding, literature, music, and the visual arts, with studies completed through multiple colleges, professional institutions, and continuing education programs.

Rather than following a single academic track, Duriez’s work is defined by interdisciplinary synthesis—integrating data, theory, and lived application across fields traditionally kept separate. His approach emphasizes pattern recognition, practical competency, and the translation of complex ideas into accessible frameworks.

Since 2012, he has maintained a disciplined creative and scholarly practice, producing an extensive body of work that includes academic writings, nonfiction research, fiction, children’s literature, music, and visual art. His output reflects a commitment not to credentials alone, but to demonstrable mastery through time, rigor, and application.

Duriez’s work challenges conventional boundaries of education, proposing that true expertise is measured not only in degrees earned, but in depth of practice, integration of knowledge, and sustained intellectual labor.
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