The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Toward a mathematical theory of inductive inference
Open accessAbstract
Intelligence tests occasionally require the extrapolation of an effective sequence (e.g. 1661, 2552, 3663, …) that is produced by some easily discernible algorithm. In this paper, we investigate the theoretical capabilities and limitations of a computer to infer such sequences. We design Turing machines that in principle are extremely powerful for this purpose and place upper bounds on the capabilities of machines that would do better.
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Citations
Cites
A formal theory of inductive inference. Part II
Solomonoff, R. J. (1964) · Information and Control · doi:10.1016/s0019-9958(64)90131-7 · Cited by 1,758
A formal theory of inductive inference. Part I
Solomonoff, R. J. (1964) · Information and Control · doi:10.1016/s0019-9958(64)90223-2 · Cited by 1,192
Cited by
Ballard, D. H. (1991) · Artificial Intelligence · doi:10.1016/0004-3702(91)90080-4 · Cited by 1,022
Learning to perceive and act by trial and error
Whitehead, S. D., & Ballard, D. H. (1991) · Machine Learning · doi:10.1007/bf00058926 · Cited by 300
Metadata
- Authors
- Blum, L., & Blum, M.
- Venue
- Information and Control
- Publisher
- Elsevier BV
- Published
- 1975-06
- Volume
- 28
- Issue
- 2
- Pages
- 125-155
- ISSN
- 0019-9958 (ISSN-L)
- OpenAlex
- W1993931385
- Cited by
- 670
- References
- 2
- FWCI
- 8.98
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Blum, L., & Blum, M. (1975). Toward a mathematical theory of inductive inference. Information and Control. https://doi.org/10.1016/s0019-9958(75)90261-2
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
