Foundations Of Reasoning Under Uncertainty
DOWNLOAD
Download Foundations Of Reasoning Under Uncertainty PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Foundations Of Reasoning Under Uncertainty book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Foundations Of Reasoning Under Uncertainty
DOWNLOAD
Author : Bernadette Bouchon
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-15
Foundations Of Reasoning Under Uncertainty written by Bernadette Bouchon 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 2010-01-15 with Computers categories.
This book draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Málaga, Spain. The conference brought together some of the world’s leading experts in the study of uncertainty.
Subjective Logic
DOWNLOAD
Author : Audun Jøsang
language : en
Publisher: Springer
Release Date : 2016-10-27
Subjective Logic written by Audun Jøsang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-27 with Computers categories.
This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments. The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.
Foundations Of Reasoning Under Uncertainty
DOWNLOAD
Author : Bernadette Bouchon-Meunier
language : en
Publisher: Springer
Release Date : 2010-01-11
Foundations Of Reasoning Under Uncertainty written by Bernadette Bouchon-Meunier and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-11 with Technology & Engineering categories.
Uncertainty exists almost everywhere, except in the most idealized situations; it is not only an inevitable and ubiquitous phenomenon, but also a fundamental sci- ti?c principle. Furthermore, uncertainty is an attribute of information and, usually, decision-relevant information is uncertain and/or imprecise, therefore the abilities to handle uncertain information and to reason from incomplete knowledge are c- cial features of intelligent behaviour in complex and dynamic environments. By carefully exploiting our tolerance for imprecision and approximation we can often achieve tractability, robustness, and better descriptions of reality than traditional - ductive methods would allow us to obtain. In conclusion, as we move further into the ageofmachineintelligence,theproblemofreasoningunderuncertainty,in other words, drawing conclusions from partial knowledge, has become a major research theme. Not surprisingly,the rigoroustreatment of uncertaintyrequiressophisticated - chinery, and the present volume is conceived as a contribution to a better und- standing of the foundations of information processing and decision-making in an environment of uncertainty, imprecision and partiality of truth. This volume draws on papers presented at the 2008 Conference on Information Processing and Management of Uncertainty (IPMU), held in Malaga, ́ Spain, or- nized by the University of Mal ́ aga. The conference brought together some of the world’s leading experts in the study of uncertainty.
Symbolic And Quantitative Approaches To Reasoning With Uncertainty
DOWNLOAD
Author : Weiru Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-24
Symbolic And Quantitative Approaches To Reasoning With Uncertainty written by Weiru Liu 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 2011-06-24 with Computers categories.
This book constitutes the refereed proceedings of the 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011, held in Belfast, UK, in June/July 2011. The 60 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on argumentation; Bayesian networks and causal networks; belief functions; belief revision and inconsistency handling; classification and clustering; default reasoning and logics for reasoning under uncertainty; foundations of reasoning and decision making under uncertainty; fuzzy sets and fuzzy logic; implementation and applications of uncertain systems; possibility theory and possibilistic logic; and uncertainty in databases.
On Foundations Of Reasoning With Uncertain Facts And Vague Concepts
DOWNLOAD
Author : Peter Schefe
language : de
Publisher:
Release Date : 1979
On Foundations Of Reasoning With Uncertain Facts And Vague Concepts written by Peter Schefe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with categories.
Probabilistic Reasoning In Intelligent Systems
DOWNLOAD
Author : Judea Pearl
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Probabilistic Reasoning In Intelligent Systems written by Judea Pearl and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Symbolic And Quantitative Approaches To Reasoning With Uncertainty
DOWNLOAD
Author : Claudio Sossai
language : en
Publisher: Springer
Release Date : 2009-06-05
Symbolic And Quantitative Approaches To Reasoning With Uncertainty written by Claudio Sossai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-05 with Computers categories.
This book constitutes the refereed proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2009, held in Verona, Italy, July 1-3, 2009. There are 76 revised full papers presented together with 3 invited lectures by three outstanding researchers in the area. All papers were carefully reviewed and selected from 118 submissions for inclusion in the book. The papers are organized in topical sections on algorithms for uncertain inference, argumentation systems, Bayesian networks, Belief functions, Belief revision and inconsistency handling, classification and clustering, conditioning, independence, inference, default reasoning, foundations of reasoning, decision making under uncertainty, Fuzzy sets and Fuzzy logic, implementation and application of uncertain systems, logics for reasoning under uncertainty, Markov decision process, and Mathematical Fuzzy Logic.
Probabilistic Reasoning In Intelligent Systems
DOWNLOAD
Author : Judea Pearl
language : en
Publisher:
Release Date : 2014
Probabilistic Reasoning In Intelligent Systems written by Judea Pearl and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Mathematics categories.
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Logical Foundations Of Artificial Intelligence
DOWNLOAD
Author : Michael R. Genesereth
language : en
Publisher: Morgan Kaufmann
Release Date : 2012-07-05
Logical Foundations Of Artificial Intelligence written by Michael R. Genesereth and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-05 with Computers categories.
Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.
Inferential Models
DOWNLOAD
Author : Ryan Martin
language : en
Publisher: CRC Press
Release Date : 2015-09-25
Inferential Models written by Ryan Martin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-25 with Mathematics categories.
A New Approach to Sound Statistical ReasoningInferential Models: Reasoning with Uncertainty introduces the authors' recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaning