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Approaching the general quantification of functional information.

Robert Kudelić1

  • 1University of Zagreb Faculty of Organization and Informatics, Varaždin, Republic of Croatia. robert.kudelic@foi.unizg.hr.

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This study introduces a novel method for quantifying functional information and its semantics. This approach offers a general framework with potential applications across various scientific disciplines, including computer science and quantum physics.

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Area of Science:

  • Computer and Information Science
  • Quantum Physics
  • Chemistry

Background:

  • Information's pivotal role is increasingly significant in the digital, AI, and big data eras.
  • Quantifying the functionality and semantics of information is a key scientific inquiry.
  • Existing approaches to information quantification present challenges.

Purpose of the Study:

  • To review state-of-the-art methods for information quantification.
  • To address challenges in quantifying functional information.
  • To propose a novel, general approach for information quantification.

Main Methods:

  • Constructive and critical review of current information quantification techniques.
  • Development of a new methodology for general functional information quantification.
  • Initial integration of functional information within a computational complexity framework.

Main Results:

  • A general method for quantifying functional information, including total system information and semantics.
  • Identification of challenges in current information quantification approaches.
  • Foundation laid for algorithmic development in functional information, exploring optimality and computational complexity.

Conclusions:

  • The developed method provides a general approach to quantifying functional information and its semantics.
  • This quantification method has broad potential significance in diverse scientific fields.
  • Establishing a computational complexity framework for functional information opens avenues for algorithmic research.