Uncertain Knowledge
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Uncertain Knowledge
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Author : Riki G. A. Dolby
language : en
Publisher: Cambridge University Press
Release Date : 2002-04-18
Uncertain Knowledge written by Riki G. A. Dolby and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-18 with Philosophy categories.
This book explores the image of science in the modern world.
Uncertain Knowledge
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Author : Dallas George Denery
language : en
Publisher:
Release Date : 2014
Uncertain Knowledge written by Dallas George Denery and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Belief and doubt categories.
The contents of this book cover uncertainty and deception in the medieval and early modern court, living with uncertainty, uncertainty in the study of the Bible, the merits of not knowing, vernacular opinions, and much more.
Representing Uncertain Knowledge
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Author : Paul Krause
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Representing Uncertain Knowledge written by Paul Krause and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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.
Discovery And Fusion Of Uncertain Knowledge In Data
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Author : Yue Kun
language : en
Publisher: World Scientific
Release Date : 2017-09-28
Discovery And Fusion Of Uncertain Knowledge In Data written by Yue Kun and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-28 with Computers categories.
Data analysis is of upmost importance in the mining of big data, where knowledge discovery and inference are the basis for intelligent systems to support the real world applications. However, the process involves knowledge acquisition, representation, inference and data, Bayesian network (BN) is the key technology plays a key role in knowledge representation, in order to pave way to cope with incomplete, fuzzy data to solve the real-life problems. This book presents Bayesian network as a technology to support data-intensive and incremental learning in knowledge discovery, inference and data fusion in uncertain environment. Contents: IntroductionData-Intensive Learning of Uncertain KnowledgeData-Intensive Inferences of Large-Scale Bayesian NetworksUncertain Knowledge Representation and Inference for Lineage Processing over Uncertain DataUncertain Knowledge Representation and Inference for Tracing Errors in Uncertain DataFusing Uncertain Knowledge in Time-Series DataSummary Readership: Graduate students, researchers and professionals in the field of artificial intelligence/machine learning and information sciences, especially in databases. Keywords: Uncertain Knowledge;Bayesian Network;Data-Intensive Computing;Lineage;Inference;FusionReview: Key Features: Upon the preliminaries of BN (Pearl, 1988), this book establishes the connection between massive/uncertain/dynamic data management and uncertainty in artificial intelligence, specifically taking BN as the knowledge framework; different from the publications (Pearl, 1988; Russel & Norvig, 2010), this book concerns uncertain knowledge representation and corresponding inferences from the data-driven perspective, where we focus on the construction of knowledge models with respect to specific applications; different from the publication (Han, 2011), this book focuses on the critical problem of knowledge engineering specially taking BN as the framework, instead of the previously-unknown patterns by mining dataThis book presents the theoretic conclusions, algorithmic strategies, running examples and empirical studies while emphasizing the soundness in both theoretic/semantic and executive/applicable perspectives of the methods for discovery and fusion of uncertain knowledge in dataThis book is appropriately a reference book for researchers in the fields of massive data analysis, artificial intelligence and knowledge engineering. As well, this book can be also adopted as textbook for graduate students who major in data mining and knowledge discovery, or intelligent data analysis etc.
Knowledge In An Uncertain World
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Author : Jeremy Fantl
language : en
Publisher: Oxford University Press
Release Date : 2009-11-05
Knowledge In An Uncertain World written by Jeremy Fantl and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-11-05 with Language Arts & Disciplines categories.
This study explores the relation between knowledge, reasons and justification. It argues that you can rely on what you know, since what you know can be a reason you have and you can rely on your reasons. But the assumption that knowledge allows for a chance of error makes this a controversial position in epistemology.
Uncertainty Analysis In Engineering And Sciences Fuzzy Logic Statistics And Neural Network Approach
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Author : Bilal M. Ayyub
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Uncertainty Analysis In Engineering And Sciences Fuzzy Logic Statistics And Neural Network Approach written by Bilal M. Ayyub and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.
Knowledge Acquisition Modeling And Management
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Author : Dieter Fensel
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-05-19
Knowledge Acquisition Modeling And Management written by Dieter Fensel and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-19 with Computers categories.
This book constitutes the refereed proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW '99, held at Dagstuhl Castle, Germany in May 1999. The volume presents 16 revised full papers and 15 revised short papers were carefully reviewed and selected form a high number of submissions. Also included are two invited papers. The papers address issues of knowledge acquisition (i.e., the process of extracting, creating, structuring knowledge, etc.), of knowledge-level modeling for knowledge-based systems, and of applying and redefining this work in a knowledge management and knowledge engineering context.
Current Trends In Knowledge Acquisition
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Author : Bob Wielinga
language : en
Publisher: IOS Press
Release Date : 1990
Current Trends In Knowledge Acquisition written by Bob Wielinga and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.
Computational Science Iccs 2008
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Author : Marian Bubak
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-11
Computational Science Iccs 2008 written by Marian Bubak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-11 with Computers categories.
The three-volume set LNCS 5101-5103 constitutes the refereed proceedings of the 8th International Conference on Computational Science, ICCS 2008, held in Krakow, Poland in June 2008. The 167 revised papers of the main conference track presented together with the abstracts of 7 keynote talks and the 100 revised papers from 14 workshops were carefully reviewed and selected for inclusion in the three volumes. The main conference track was divided into approximately 20 parallel sessions addressing topics such as e-science applications and systems, scheduling and load balancing, software services and tools, new hardware and its applications, computer networks, simulation of complex systems, image processing and visualization, optimization techniques, numerical linear algebra, and numerical algorithms. The second volume contains workshop papers related to various computational research areas, e.g.: computer graphics and geometric modeling, simulation of multiphysics multiscale systems, computational chemistry and its applications, computational finance and business intelligence, physical, biological and social networks, geocomputation, and teaching computational science. The third volume is mostly related to computer science topics such as bioinformatics' challenges to computer science, tools for program development and analysis in computational science, software engineering for large-scale computing, collaborative and cooperative environments, applications of workflows in computational science, as well as intelligent agents and evolvable systems.
Uncertainty Reasoning For The Semantic Web Ii
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Author : Fernando Bobillo
language : en
Publisher: Springer
Release Date : 2013-01-09
Uncertainty Reasoning For The Semantic Web Ii written by Fernando Bobillo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-09 with Computers categories.
This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2008, 2009, and 2010 or presented at the first international Workshop on Uncertainty in Description Logics (UniDL), held at the Federated Logic Conference (FLoC) in 2010. The 17 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.