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                <identifier>oai:data.mendeley.com/gnrmxwhc6v.1</identifier>
                <datestamp>2025-06-26T09:53:32Z</datestamp>
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    <dc:creator>Bozhilov, Dobri</dc:creator>
    <dc:title>The Concept of NP-Completeness Introduces a Statistical Argument Against P=NP</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>The concept of NP-completeness summarizes a multitude of problems that can be transformed into each other through polynomial reduction. Its main idea is: &quot;if we solve one problem in polynomial time, we will solve them all.&quot; At first glance, this is promising. But upon closer analysis, it turns out that the mechanism of reduction itself requires that each NP-complete problem has an independent polynomial-time solution. This is because the reduction represents a transition between initially necessary solutions for each separate problem, and not a means to simplify the solution by finding it in only one place. Therefore, with each new proven NP-complete problem, the necessity for a solution to exist for it is added, if such a solution is even possible. If even one does not have a solution, then none can. Thus, a statistical argument against P=NP is formed.</dc:description>
    <dc:subject>Algorithms</dc:subject>
    <dc:subject>Computational Complexity</dc:subject>
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    <dc:identifier>doi:10.17632/gnrmxwhc6v.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/gnrmxwhc6v.1</dc:identifier>
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    <dc:date>2025-06-26T09:53:32Z</dc:date>
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