Cited by 25Computability, Logic, AI AlgorithmsPsychiatry, Mental Health, NeuroscienceArtificial Intelligence Applications

On the Limits of Recursively Self-Improving AGI

Yampolskiy, Roman V.·2015·Lecture Notes in Computer Science

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Crossref · 10.1007/978-3-319-21365-1_40

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50 of 50 references verified0 citation errors · 0 not checkable

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  • A system capable of complete self-referential at the outset may lose this capability as it evolves.

    “Consequently, a system capable of complete self-referential at the outset may lose this capability as it evolves (Yampolskiy, 2015).”
  • A system capable of complete self-referential at the outset may lose this capability as it evolves.

    “Consequently, a system capable of complete self-referential at the outset may lose this capability as it evolves (Yampolskiy, 2015).”
  • As the agent system becomes increasingly complex through self-optimization, it may require exponentially more intelligence to understand itself.

    “Additionally, as the agent system becomes increasingly complex through self-optimization, it may require exponentially more intelligence to understand itself.”

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Authors
Yampolskiy, R. V.
Affiliations
University of Louisville (US)
Corresponding author
Yampolskiy, Roman V.
Venue
Lecture Notes in Computer Science
Published
2015
Pages
394-403
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2406968617
Cited by
23
References
54
Citations by year
2026: 3 · 2023: 1 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 3 · 2018: 2 · 2017: 2 · 2016: 4 · 2015: 2
FWCI
3.00
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
  • Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
artificial general intelligence, limits of computation, convergence theory, self-improving AI

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