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A formal theory of inductive inference. Part II
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“The ability to generalise is closely related to compression [14,15], with more compressed representations yielding better accuracy [13] for the same reason that there is only one straight line interpolating any two points, but infinitely many polynomials of higher degree.”
From Compression, The Fermi Paradox and Artificial Super-Intelligence (2022) · cites this paper as [15]
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Metadata
- Authors
- Solomonoff, R. J.
- Corresponding author
- Solomonoff, R.J.
- Venue
- Information and Control
- Publisher
- Elsevier BV
- Published
- 1964-06
- Volume
- 7
- Issue
- 2
- Pages
- 224-254
- ISSN
- 0019-9958 (ISSN-L)
- OpenAlex
- W2135625884
- Cited by
- 1,758
- References
- 6
- Citations by year
- 2026: 43 · 2025: 16 · 2024: 18 · 2023: 22 · 2022: 35 · 2021: 52 · 2020: 60 · 2019: 40 · 2018: 60 · 2017: 67 · 2016: 64 · 2015: 75 · 2014: 59 · 2013: 94 · 2012: 88
- FWCI
- 1.52
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Information and Control (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Physical Sciences › Computer Science › Computational Theory and Mathematics › semigroups and automata theory
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Keywords
- inductive reasoning, universal Turing machine, phrase structure grammar, prediction accuracy
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