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In algorithmic information theory, algorithmic probability, also known as Solomonoff probability, is a mathematical method of assigning a prior probability to a given observation. It was invented by Ray Solomonoff in the 1960s. It is used in inductive inference theory and analyses of algorithms. In his general theory of … 展开
Algorithmic probability is the main ingredient of Solomonoff's theory of inductive inference, the theory of prediction based on observations; it was invented with the goal of using it for machine learning; given … 展开
Solomonoff invented the concept of algorithmic probability with its associated invariance theorem around 1960, publishing a report on it: "A Preliminary Report on a General … 展开
I. Kolmogorov's Invariance Theorem
Kolmogorov's Invariance theorem clarifies that the Kolmogorov Complexity, or Minimal Description Length, of a dataset is invariant to the choice of Turing-Complete language used to simulate a Universal Turing Machine: 展开• Rathmanner, S and Hutter, M., "A Philosophical Treatise of Universal Induction" in Entropy 2011, 13, 1076-1136: A very clear philosophical … 展开
CC-BY-SA 许可证中的维基百科文本 Probabilistic analysis of algorithms - Wikipedia
In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm. This approach is not the same as that of probabilistic algorithms, but the two may be combined.
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Randomized algorithm - Wikipedia
- As a motivating example, consider the problem of finding an ‘a’ in an array of nelements. Input: An array of n≥2 elements, in which half are ‘a’s and the other half are ‘b’s. Output: Find an ‘a’ in the array. We give two versions of the algorithm, one Las Vegas algorithm and one Monte Carlo algorithm. Las Vegas algorithm: This algorithm succeeds wi...
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Algorithmic Probability - Lark
网页2023年12月26日 · Algorithmic probability, often referred to as algorithmic randomness or algorithmic complexity, is a crucial concept in the field of artificial intelligence, providing …
Algorithmic probability - Scholarpedia
网页2015年9月3日 · Algorithmic "Solomonoff" Probability (AP) assigns to objects an a priori probability that is in some sense universal. This prior distribution has theoretical …
Algorithmic Probability: Theory and Applications | SpringerLink
网页We first define Algorithmic Probability, an extremely powerful method of inductive inference. We discuss its completeness, incomputability, diversity and subjectivity and …
网页Algorithmic Probability is a relatively recent definition of probability that attempts to solve these problems. We begin with a simple discussion of prediction and its …
Algorithmic Probability - SpringerLink
网页In probability theory one starts with the assumption that we have a sample space x of outcomes, with a probability distribution x. This x is either discovered empirically or …
网页This volume collects cutting-edge research and expository on algorithmic probability and combinatorics. It includes contributions by well-established experts and younger
Ray Solomonoff's Home Page
网页Inventor of Algorithmic Probability and The General Theory of Inductive Inference Father of Algorithmic Information Theory Ray's beautiful formula Obituary by Paul Vitanyi; …
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