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Uncertainty in Knowledge Bases

Uncertainty in Knowledge Bases
Author: Bernadette Bouchon-Meunier
Publisher: Springer Science & Business Media
Total Pages: 630
Release: 1991-09-11
Genre: Computers
ISBN: 9783540543466

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One out of every two men over eigthy suffers from carcinoma of the prostate.It is discovered incidentally in many patients with an alleged benign prostatic hyperplasia. In treating patients, the authors make clear that primary radical prostatectomy is preferred over transurethral resection due to the lower complication rate.


Uncertainty and Vagueness in Knowledge Based Systems

Uncertainty and Vagueness in Knowledge Based Systems
Author: Rudolf Kruse
Publisher: Springer Science & Business Media
Total Pages: 495
Release: 2012-12-06
Genre: Computers
ISBN: 3642767028

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The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.


Uncertainty in Knowledge Bases

Uncertainty in Knowledge Bases
Author: Bernadette Bouchon-Meunier
Publisher:
Total Pages: 624
Release: 2014-01-15
Genre:
ISBN: 9783662186640

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Uncertainty in Knowledge-Based Systems

Uncertainty in Knowledge-Based Systems
Author: Bernadette Bouchon-Meunier
Publisher: Springer Science & Business Media
Total Pages: 420
Release: 1987-11-04
Genre: Computers
ISBN: 9783540185796

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Knowledge Representation and Reasoning Under Uncertainty

Knowledge Representation and Reasoning Under Uncertainty
Author: Michael Masuch
Publisher: Springer Science & Business Media
Total Pages: 252
Release: 1994-06-28
Genre: Computers
ISBN: 9783540580959

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This volume is based on the International Conference Logic at Work, held in Amsterdam, The Netherlands, in December 1992. The 14 papers in this volume are selected from 86 submissions and 8 invited contributions and are all devoted to knowledge representation and reasoning under uncertainty, which are core issues of formal artificial intelligence. Nowadays, logic is not any longer mainly associated to mathematical and philosophical problems. The term applied logic has a far wider meaning, as numerous applications of logical methods, particularly in computer science, artificial intelligence, or formal linguistics, testify. As demonstrated also in this volume, a variety of non-standard logics gained increased importance for knowledge representation and reasoning under uncertainty.


A Methodology for Uncertainty in Knowledge-Based Systems

A Methodology for Uncertainty in Knowledge-Based Systems
Author: Kurt Weichselberger
Publisher: Lecture Notes in Artificial Intelligence
Total Pages: 154
Release: 1990-03-07
Genre: Computers
ISBN:

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In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.


Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications
Author: Jesús Medina
Publisher: Springer
Total Pages: 773
Release: 2018-05-29
Genre: Computers
ISBN: 3319914790

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This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).