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Uncertainty In Knowledge Bases
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Author :Bernadette Bouchon-Meunier Publisher :Springer Science & Business Media ISBN 13 :9783540543466 Total Pages :630 pages Book Rating :4.5/5 (434 download)
Book Synopsis Uncertainty in Knowledge Bases by : Bernadette Bouchon-Meunier
Download or read book Uncertainty in Knowledge Bases written by Bernadette Bouchon-Meunier and published by Springer Science & Business Media. This book was released on 1991-09-11 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Uncertainty in Knowledge Bases by : Bernadette Bouchon-Meunier
Download or read book Uncertainty in Knowledge Bases written by Bernadette Bouchon-Meunier and published by . This book was released on 2014-01-15 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Uncertainty and Vagueness in Knowledge Based Systems by : Rudolf Kruse
Download or read book Uncertainty and Vagueness in Knowledge Based Systems written by Rudolf Kruse and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author :Bernadette Bouchon-Meunier Publisher :Springer Science & Business Media ISBN 13 :9783540185796 Total Pages :420 pages Book Rating :4.1/5 (857 download)
Book Synopsis Uncertainty in Knowledge-Based Systems by : Bernadette Bouchon-Meunier
Download or read book Uncertainty in Knowledge-Based Systems written by Bernadette Bouchon-Meunier and published by Springer Science & Business Media. This book was released on 1987-11-04 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Davide Ciucci
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Davide Ciucci and published by Springer Nature. This book was released on 2022-07-04 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Marie-Jeanne Lesot
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Marie-Jeanne Lesot and published by Springer Nature. This book was released on 2020-06-05 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Eyke Hüllermeier
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Eyke Hüllermeier and published by Springer Science & Business Media. This book was released on 2010-06-25 with total page 786 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on Information Processing and Management of - certainty in Knowledge-Based Systems, IPMU, is organized every two years with the aim of bringing together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, this conference has been providing a forum for the exchange of ideas between th theoreticians and practitioners working in these areas and related ?elds. The 13 IPMU conference took place in Dortmund, Germany, June 28–July 2, 2010. This volume contains 79 papers selected through a rigorous reviewing process. The contributions re?ect the richness of research on topics within the scope of the conference and represent several important developments, speci?cally focused on theoretical foundations and methods for information processing and management of uncertainty in knowledge-based systems. We were delighted that Melanie Mitchell (Portland State University, USA), Nihkil R. Pal (Indian Statistical Institute), Bernhard Sch ̈ olkopf (Max Planck I- titute for Biological Cybernetics, Tubing ̈ en, Germany) and Wolfgang Wahlster (German Research Center for Arti?cial Intelligence, Saarbruc ̈ ken) accepted our invitations to present keynote lectures. Jim Bezdek received the Kamp ́ede F ́ eriet Award, granted every two years on the occasion of the IPMU conference, in view of his eminent research contributions to the handling of uncertainty in clustering, data analysis and pattern recognition.
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems by : Joao Paulo Carvalho
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems written by Joao Paulo Carvalho and published by Springer. This book was released on 2016-06-10 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set (CCIS 610 and 611) constitute the proceedings of the 16th International Conference on Information processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2016, held in Eindhoven, The Netherlands, in June 2016. The 127 revised full papers presented together with four invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy measures and integrals; uncertainty quantification with imprecise probability; textual data processing; belief functions theory and its applications; graphical models; fuzzy implications functions; applications in medicine and bioinformatics; real-world applications; soft computing for image processing; clustering; fuzzy logic, formal concept analysis and rough sets; graded and many-valued modal logics; imperfect databases; multiple criteria decision methods; argumentation and belief revision; databases and information systems; conceptual aspects of data aggregation and complex data fusion; fuzzy sets and fuzzy logic; decision support; comparison measures; machine learning; social data processing; temporal data processing; aggregation.
Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations by : Jesús Medina
Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations written by Jesús Medina and published by Springer. This book was released on 2018-05-30 with total page 835 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Book Synopsis Uncertainty in Knowledge Bases by : B. Bouchon-Meunier
Download or read book Uncertainty in Knowledge Bases written by B. Bouchon-Meunier and published by . This book was released on 1991 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Uncertainty Models for Knowledge-based Systems by : Irwin R. Goodman
Download or read book Uncertainty Models for Knowledge-based Systems written by Irwin R. Goodman and published by North Holland. This book was released on 1985 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Uncertainty in Knowledge-Based Systems by : Bernadette Bouchon
Download or read book Uncertainty in Knowledge-Based Systems written by Bernadette Bouchon and published by . This book was released on 2014-01-15 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Knowledge Representation and Reasoning Under Uncertainty by : Michael Masuch
Download or read book Knowledge Representation and Reasoning Under Uncertainty written by Michael Masuch and published by Springer Science & Business Media. This book was released on 1994-06-28 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Methodology for Uncertainty in Knowledge-Based Systems by : Kurt Weichselberger
Download or read book A Methodology for Uncertainty in Knowledge-Based Systems written by Kurt Weichselberger and published by Lecture Notes in Artificial Intelligence. This book was released on 1990-03-07 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Representing Uncertain Knowledge by : Paul Krause
Download or read book Representing Uncertain Knowledge written by Paul Krause and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for malisms. In this book, we offer a broad perspective on uncertainty and approach es to managing uncertainty. Rather than provide a daunting mass of techni cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di rections in the field. The intended readership will include researchers and practitioners in volved in the design and implementation of Decision Support Systems, Ex pert Systems, other Knowledge-Based Systems and in Cognitive Science.
Book Synopsis A Methodology for Uncertainty in Knowledge-Based Systems by : Kurt Weichselberger
Download or read book A Methodology for Uncertainty in Knowledge-Based Systems written by Kurt Weichselberger and published by . This book was released on 2014-01-15 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Uncertainty in Artificial Intelligence by : David Heckerman
Download or read book Uncertainty in Artificial Intelligence written by David Heckerman and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
