所罗门诺夫的归纳推理理论

所罗门诺夫的归纳推理理论（Solomonoff's theory of inductive inference）是对奥卡姆剃刀叙述的数学化描述。[1][2][3][4][5]该理论指出：在所有能够完全描述的已观测的可计算类中，较短的可计算理论在估计下一次观测结果的概率时具有较大的权重。简而言之，在几组可以给出的答案的假设论述中，假设越少的越被大家选择。引申为“越简单的越易行”。

参考资料

JJ McCall. Induction: From Kolmogorov and Solomonoff to De Finetti and Back to Kolmogorov – Metroeconomica, 2004 – Wiley Online Library.
D Stork. Foundations of Occam's razor and parsimony in learning from ricoh.com – NIPS 2001 Workshop, 2001
A.N. Soklakov. Occam's razor as a formal basis for a physical theory from arxiv.org – Foundations of Physics Letters, 2002 – Springer
Jose Hernandez-Orallo. (PDF). Journal of Logic, Language and Information. 1999, 9 [2018-07-31]. （原始内容存档 (PDF)于2018-10-09）.
M Hutter. On the existence and convergence of computable universal priors arxiv.org – Algorithmic Learning Theory, 2003 – Springer

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[ReferenceA-1] JJ McCall. Induction: From Kolmogorov and Solomonoff to De Finetti and Back to Kolmogorov – Metroeconomica, 2004 – Wiley Online Library.

[ReferenceB-2] D Stork. Foundations of Occam's razor and parsimony in learning from ricoh.com – NIPS 2001 Workshop, 2001

[ReferenceC-3] A.N. Soklakov. Occam's razor as a formal basis for a physical theory from arxiv.org – Foundations of Physics Letters, 2002 – Springer

[Hernandez.1999-4] Jose Hernandez-Orallo. (PDF). Journal of Logic, Language and Information. 1999, 9 [2018-07-31]. （原始内容存档 (PDF)于2018-10-09）.

[Hutter.2003-5] M Hutter. On the existence and convergence of computable universal priors arxiv.org – Algorithmic Learning Theory, 2003 – Springer