Solomonoff j (4 Ergebnisse)

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    • Sprache: Englisch

      Verlag: Texas A&M University Press, 2000

      0890969019 / 9780890969014

      • Hardcover

      Anbieter: Books From California, Simi Valley, CA, USABooks From California

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      Zustand: Gebraucht - Befriedigend

      EUR 27,88

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      hardcover. Zustand: Good. Zustand des Schutzumschlags: Includes dust jacket. Ex-library copy with stamps and stickers. The copy shows minor external wear, but is in otherwise clean condition.

    • Verlag: Kegan Paul, Trench, Trubner, 1916

      • Hardcover

      Anbieter: World of Rare Books, Goring-by-Sea, SXW, Vereinigtes KönigreichWorld of Rare Books

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      EUR 20,43

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      In den Warenkorb

      Zustand: Good. 1916. No Edition Stated. Unpaginated. No dust jacket. Blue cloth with gilt lettering. Three parts in one book, thus unpaginated. Pages are lightly tanned and thumbed at the edges, with light foxing. Binding has remained firm. Boards are a little rub worn, slight shelf wear to corners, spine and edges. Corners are a little bumped. Spine ends are mildly crushed. Light tanning to spine and edges. Boards are slightly bowed. Slight forward lean to text block.

      • Hardcover

      Anbieter: Anthony C. Hall, Bookseller ABA ILAB, Isleworth, MIDDX, Vereinigtes KönigreichAnthony C. Hall, Bookseller ABA ILAB

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      Verbandsmitglied: ABAPBFAILAB

      Zustand: Gebraucht

      EUR 36,06

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      In den Warenkorb

      Hardback. viii, 131pp many illustrations, Kegan Paul, London (1917) Very good copy with a depiction of a Russian classroom on the front cover.

    • Verlag: Academic Press, New York, 1964

      • Softcover
      • Erstausgabe

      Anbieter: Jeremy Norman's historyofscience, Novato, CA, USAJeremy Norman's historyofscience

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      EUR 763,38

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      In den Warenkorb

      Solomonoff, Ray R. (1926-2009). A formal theory of inductive inference. Part I [II]. In Information and Control 7 (1964): 1-22; 224-254. Whole volume. 221 x 141 mm. Library buckram. Very good. First Edition, journal issue. Solomonoff was a founder of the branch of AI based on machine learning, prediction and probability. He invented algorithmic probability, a mathematical method of assigning a prior probability to a given observation. He introduced this concept in a preliminary report published in 1960 and gave it a much fuller treatment in the present two-part paper, which is considered the beginning of algorithmic information theory. Prior to the 1960s, the usual method of calculating probability was based on frequency: taking the ratio of favorable results to the total number of trials. In his 1960 publication, and, more completely, in his 1964 publications, Solomonoff seriously revised this definition of probability. He called this new form of probability "Algorithmic Probability" and showed how to use it for prediction in his theory of inductive inference. As part of this work, he produced the philosophical foundation for the use of Bayes rule of causation for prediction [a method now known as Solomonoff's induction] . . . In the years following his discovery of Algorithmic Probability he focused on how to use this probability and Solomonoff Induction in actual prediction and problem solving for A.I. (Wikipedia article on Solomonoff). Solomonoff was one of the original 11 attendees at the 1956 Dartmouth Summer Research Conference on Artificial Intelligence, which introduced AI as a science. .