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An Information Framework of Intelligence.

Michael E Hochberg1

  • 1ISEM, Université de Montpellier, CNRS, IRD, EPHE, 34095 Montpellier, France; Santa Fe Institute, Santa Fe, NM 87501, USA.

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Summary
This summary is machine-generated.

This study introduces an Information Framework of Intelligence (IFI) applicable across all systems. It quantifies intelligence by measuring acquired goal-useful information, offering a new approach to understanding intelligence evolution and constraints.

Keywords:
ComplexityDifficultyEvolutionInformationIntelligence nichePredictionUncertainty

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Area of Science:

  • Theoretical Physics
  • Cognitive Science
  • Artificial Intelligence
  • Evolutionary Biology

Background:

  • Intelligence is a complex human construct with numerous definitions and elusive quantification.
  • Existing theories and indicators of intelligence lack a unified, universally applicable framework.
  • Understanding intelligence requires both theoretical grounding and measurable quantification.

Purpose of the Study:

  • To present a novel Information Framework of Intelligence (IFI) applicable across diverse systems (physics, biology, AI).
  • To introduce the concept of the "intelligence niche" for understanding intelligence constraints and evolution.
  • To develop quantitative indicators for measuring intelligence based on observable phenomena.

Main Methods:

  • Developed the Information Framework of Intelligence (IFI) with a focus on information processing.
  • Introduced the "intelligence niche" as a conceptual tool for analyzing intelligence.
  • Proposed a classification of intelligence levels and scales.
  • Defined quantitative indicators of intelligence based on subgoal identification and resolution.

Main Results:

  • The IFI provides a unified approach to intelligence across physics, biology, humans, and AI.
  • The "intelligence niche" offers a basis for understanding intelligence evolution and constraints.
  • Quantitative indicators measure intelligence via acquired goal-useful information relative to goal complexity or difficulty.
  • Intelligence is conceptualized as a real-time calculus of information processing and prediction.

Conclusions:

  • The IFI offers a robust, quantifiable framework for intelligence applicable across all systems.
  • The "intelligence niche" provides novel insights into the evolution and constraints of intelligence.
  • The proposed quantitative indicators allow for measurable assessment of intelligence.
  • IFI has significant implications for future research in intelligence across scientific domains.