Solomonoff J (9 results)

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Condition: 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.…

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

Leatherbound. Condition: NEW. BOOKS ARE EXEMPT FROM IMPORT DUTIES AND TARIFFS; NO EXTRA CHARGES APPLY. Leatherbound edition. Condition: New. Leather Binding on Spine and Corners with Golden leaf printing on spine. Bound in genuine leather with Satin ribbon page markers and Spine with raised gilt bands. Pages: 168. A perfect gift for your loved ones. Reprinted from 1916 edition. NO changes have been made to the original text. This is NOT a retyped or an ocr'd reprint. Illustrations, Index, if any, are included in black and white. Each page is checked manually before printing. As this print on demand book is reprinted from a very old book, there could be some missing or flawed pages, but we always try to make the book as complete as possible. Fold-outs, if any, are not part of the book. If the original book was published in multiple volumes then this reprint is of only one volume, not the whole set. IF YOU WISH TO ORDER PARTICULAR VOLUME OR ALL THE VOLUMES YOU CAN CONTACT US. Resized as per current standards. Sewing binding for longer life, where the book block is actually sewn (smythe sewn/section sewn) with thread before binding which results in a more durable type of binding. Volume V1-3 Language: English Pages: 168 Volume V1-3.…

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. . …