Uncertainty In Artificial Intelligence 2

Author : L.N. Kanal
Publisher : Elsevier
ISBN 13 : 1483296539
Total Pages : 474 pages
Book Rating : 4.31/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence 2 written by L.N. Kanal and published by Elsevier. This book was released on 2014-06-28 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second volume is arranged in four sections: Analysis contains papers which compare the attributes of various approaches to uncertainty. Tools provides sufficient information for the reader to implement uncertainty calculations. Papers in the Theory section explain various approaches to uncertainty. The Applications section describes the difficulties involved in, and the results produced by, incorporating uncertainty into actual systems.

Author : Deyi Li
Publisher : CRC Press
ISBN 13 : 1498776272
Total Pages : 290 pages
Book Rating : 4.71/5 ( download)

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Download or read book Artificial Intelligence with Uncertainty written by Deyi Li and published by CRC Press. This book was released on 2017-05-18 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural language – the carrier of knowledge and intelligence, and introduce efficient physical methods for data mining amd control. In this new edition, we have more in-depth description of the models and methods, of which the mathematical properties are proved strictly which make these theories and methods more complete. The authors also highlight their latest research results.

Author : Laveen N. Kanal
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.73/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by Laveen N. Kanal and published by . This book was released on 1988 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : F. Stadler
Publisher : Springer Science & Business Media
ISBN 13 : 1402021968
Total Pages : 355 pages
Book Rating : 4.61/5 ( download)

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Download or read book Induction and Deduction in the Sciences written by F. Stadler and published by Springer Science & Business Media. This book was released on 2004-04-30 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles in this volume deal with the main inferential methods that can be applied to different kinds of experimental evidence. These contributions - accompanied with critical comments - by renowned scholars in the field of philosophy of science aim at removing the traditional opposition between inductivists and deductivists. They explore the different methods of explanation and justification in the sciences in different contexts and with different objectives. The volume contains contributions on methods of the sciences, especially on induction, deduction, abduction, laws, probability and explanation, ranging from logic, mathematics, natural to the social sciences. They present a highly topical pluralist re-evaluation of methodological and foundational procedures and reasoning, e.g. focusing in Bayesianism and Artificial Intelligence. They document the second international conference in Vienna on "Induction and Deduction in the Sciences" as part of the Scientific Network on "Historical and Contemporary Perspectives of Philosophy of Science in Europe", funded by the European Science Foundation (ESF).

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.78/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : David Heckerman
Publisher : Morgan Kaufmann
ISBN 13 : 1483214516
Total Pages : 554 pages
Book Rating : 4.11/5 ( download)

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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 554 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.

Author : Didier J. Dubois
Publisher : Morgan Kaufmann
ISBN 13 : 1483282872
Total Pages : 379 pages
Book Rating : 4.79/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by Didier J. Dubois and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence: Proceedings of the Eighth Conference (1992) covers the papers presented at the Eighth Conference on Uncertainty in Artificial Intelligence, held at Stanford University on July 17-19, 1992. The book focuses on the processes, methodologies, technologies, and approaches involved in artificial intelligence. The selection first offers information on Relative Evidential Support (RES), modal logics for qualitative possibility and beliefs, and optimizing causal orderings for generating DAGs from data. Discussions focus on reversal, swap, and unclique operators, modal representation of possibility, and beliefs and conditionals. The text then examines structural controllability and observability in influence diagrams, lattice-based graded logic, and dynamic network models for forecasting. The manuscript takes a look at reformulating inference problems through selective conditioning, entropy and belief networks, parallelizing probabilistic inference, and a symbolic approach to reasoning with linguistic quantifiers. The text also ponders on sidestepping the triangulation problem in Bayesian net computations; exploring localization in Bayesian networks for large expert systems; and expressing relational and temporal knowledge in visual probabilistic networks. The selection is a valuable reference for researchers interested in artificial intelligence.

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.63/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Carole H. Sudre
Publisher : Springer Nature
ISBN 13 : 3030603652
Total Pages : 233 pages
Book Rating : 4.56/5 ( download)

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Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis written by Carole H. Sudre and published by Springer Nature. This book was released on 2020-10-05 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

Author : Laveen N. Kanal
Publisher : North Holland
ISBN 13 : 9780444700582
Total Pages : 509 pages
Book Rating : 4.87/5 ( download)

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Download or read book Uncertainty in Artificial Intelligence written by Laveen N. Kanal and published by North Holland. This book was released on 1986 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardbound. How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.