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July 26, 2026Open Access

Self-Improving AI Needs What Built Human Knowledge: Model Domains, Mappings, and Records

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Authors

YZYuxiang Zhang

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Overview

The paper argues that self-improving AI requires a structured knowledge network to solve complex problems.

Key Points

  • The research aims to define a structured framework for self-improving AI that mirrors human knowledge accumulation.
  • Identifies essential components of human knowledge: domains, mappings, and records.
  • Analyzes existing AI paradigms and their limitations regarding knowledge structures.
  • Proposes a semi-formal framework and experimental program for self-improving AI.
  • Demonstrates that effective AI systems like AlphaZero incorporate elements of the proposed knowledge network.
  • Indicates that traditional AI paradigms lack critical components for true self-improvement.
  • Suggests a necessity for AI agents to evolve a structure of models, mappings, and records.

Cite This Study

Yuxiang Zhang (2026) studied this question.

synapsesocial.com/papers/6a65a825d3aea3239cd78ac5https://doi.org/10.5281/zenodo.21523570
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  5. 5A Path to Human-Level AI through Computational Knowledge Science2024