2008, ISBN: 0387768718
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2008, ISBN: 9780387768717
A Comprehensive Framework for Uncertain Inference, Buch, Hardcover, 1st Edition. 2nd Printing. 2008, [PU: Springer-Verlag New York Inc.], Springer-Verlag New York Inc., 2008
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2008, ISBN: 0387768718
[EAN: 9780387768717], Neubuch, [PU: Springer US], FUZZY LOGIK - SET SCHLUSS (LOGISCH) WAHRSCHEINLICHKEIT WAHRSCHEINLICHKEITSTHEORIE EXPERIENTIALSEMANTICS FIRST-ORDEREXTENSIONALINFERENCE H… More...
Goertzel, Ben; Heljakka, Ari; Goertzel, Izabela Freire; Iklé, Matthew:
Probabilistic Logic Networks A Comprehensive Framework for Uncertain Inference - First edition2008, ISBN: 0387768718
Hardcover
1st Edition.2nd Printing. 2008 Gebundene Ausgabe Fuzzy Logik - Fuzzy Set, Schluss (logisch), Wahrscheinlichkeit - Wahrscheinlichkeitstheorie, Künstliche Intelligenz, fuzzy; experiential… More...
2011
ISBN: 9780387768717
Paperback
Softcover, [ED: 1], PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping ser… More...
2008, ISBN: 9780387768717
A Comprehensive Framework for Uncertain Inference, Buch, Hardcover, 1st Edition. 2nd Printing. 2008, [PU: Springer-Verlag New York Inc.], Springer-Verlag New York Inc., 2008
2008, ISBN: 0387768718
[EAN: 9780387768717], Neubuch, [PU: Springer], Clean and crisp and new!, Books
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Details of the book - Probabilistic Logic Networks
EAN (ISBN-13): 9780387768717
ISBN (ISBN-10): 0387768718
Hardcover
Paperback
Publishing year: 2008
Publisher: Springer-Verlag New York Inc.
333 Pages
Weight: 0,590 kg
Language: eng/Englisch
Book in our database since 2007-11-02T09:05:09-04:00 (New York)
Detail page last modified on 2023-10-25T18:22:26-04:00 (New York)
ISBN/EAN: 9780387768717
ISBN - alternate spelling:
0-387-76871-8, 978-0-387-76871-7
Alternate spelling and related search-keywords:
Book author: ben goertzel, freire, goertz, ikle, ari ben menashe
Book title: probabilistic, uncertain inference, logic, framework, ben
Information from Publisher
Author: Ben Goertzel; Matthew Iklé; Izabela Freire Goertzel; Ari Heljakka
Title: Probabilistic Logic Networks - A Comprehensive Framework for Uncertain Inference
Publisher: Springer; Springer US
336 Pages
Publishing year: 2008-11-11
New York; NY; US
Language: English
160,49 € (DE)
164,99 € (AT)
177,00 CHF (CH)
Available
VIII, 336 p.
BB; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Fuzzy; experiential semantics; first-order extensional inference; higher-order extensional inference; intensional inference; knowledge representation; large-scale inference; logic; probabilistic logic networks; semantics; temporal and causal inference; uncertainty; Artificial Intelligence; Mathematical Applications in Computer Science; Theoretische Informatik; BC
This book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. Going beyond prior probabilistic approaches to uncertain inference, PLN encompasses such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality. The book provides an overview of PLN in the context of other approaches to uncertain inference. Topics addressed in the text include: the basic formalism of PLN knowledge representation the conceptual interpretation of the terms used in PLN an indefinite probability approach to quantifying uncertainty, providing a general method for calculating the "weight-of-evidence" underlying the conclusions of uncertain inference specific PLN inference rules and the corresponding truth-value formulas used to determine the strength of the conclusion of an inference rule from the strengths of the premises large-scale inference strategies inference using variables indefinite probabilities involving quantifiers inheritance based on properties or patterns the Novamente Cognition Engine, an application of PLN temporal and causal logic in PLN Researchers and graduate students in artificial intelligence, computer science, mathematics and cognitive sciences will find this novel perspective on uncertain inference a thought-provoking integration of ideas from a variety of other lines of inquiry.Provides a comprehensive framework for uncertain reasoning, integrating probability theory, predicate and term logic, and pattern theory Considers a broad scope of reasoning types Fuses rigorous mathematics with practical computation to describe methods designed for large-scale and, in many cases, real-time inference within commercial software systems
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