Artificial Intelligence With Uncertainty

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Artificial Intelligence with Uncertainty

Author : Deyi Li
Publisher : CRC Press
ISBN 13 : 1498776272
Total Pages : 290 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Artificial Intelligence with Uncertainty by : Deyi Li

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.

Uncertainty in Artificial Intelligence

Author : David Heckerman
Publisher : Morgan Kaufmann
ISBN 13 : 1483214516
Total Pages : 552 pages
Book Rating : 4.4/5 (832 download)

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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.

Uncertainty and Vagueness in Knowledge Based Systems

Author : Rudolf Kruse
Publisher : Springer Science & Business Media
ISBN 13 : 3642767028
Total Pages : 495 pages
Book Rating : 4.6/5 (427 download)

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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.

The Death of Uncertainty

Author : Michael Tan
Publisher :
ISBN 13 : 9781641374026
Total Pages : pages
Book Rating : 4.3/5 (74 download)

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Book Synopsis The Death of Uncertainty by : Michael Tan

Download or read book The Death of Uncertainty written by Michael Tan and published by . This book was released on 2019-12-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Qualitative Methods for Reasoning Under Uncertainty

Author : Simon Parsons
Publisher : MIT Press
ISBN 13 : 9780262161688
Total Pages : 534 pages
Book Rating : 4.1/5 (616 download)

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Book Synopsis Qualitative Methods for Reasoning Under Uncertainty by : Simon Parsons

Download or read book Qualitative Methods for Reasoning Under Uncertainty written by Simon Parsons and published by MIT Press. This book was released on 2001 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using qualitative methods to deal with imperfect information.

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

Author : Hayit Greenspan
Publisher : Springer Nature
ISBN 13 : 3030326896
Total Pages : 192 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures by : Hayit Greenspan

Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures written by Hayit Greenspan and published by Springer Nature. This book was released on 2019-10-10 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 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. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Subjective Logic

Author : Audun Jøsang
Publisher : Springer
ISBN 13 : 3319423371
Total Pages : 337 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Subjective Logic by : Audun Jøsang

Download or read book Subjective Logic written by Audun Jøsang and published by Springer. This book was released on 2016-10-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Uncertainty in Artificial Intelligence

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (634 download)

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Book Synopsis Uncertainty in Artificial Intelligence by :

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:

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis

Author : Carole H. Sudre
Publisher : Springer Nature
ISBN 13 : 3030603652
Total Pages : 233 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis by : Carole H. Sudre

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.

Representing Uncertain Knowledge

Author : Paul Krause
Publisher : Springer Science & Business Media
ISBN 13 : 9401120846
Total Pages : 287 pages
Book Rating : 4.4/5 (11 download)

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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.

Computer Information Systems and Industrial Management

Author : Khalid Saeed
Publisher :
ISBN 13 : 9783642409264
Total Pages : 546 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Computer Information Systems and Industrial Management by : Khalid Saeed

Download or read book Computer Information Systems and Industrial Management written by Khalid Saeed and published by . This book was released on 2013-09-11 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence

Author : Melanie Mitchell
Publisher : Farrar, Straus and Giroux
ISBN 13 : 0374715238
Total Pages : 336 pages
Book Rating : 4.3/5 (747 download)

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Book Synopsis Artificial Intelligence by : Melanie Mitchell

Download or read book Artificial Intelligence written by Melanie Mitchell and published by Farrar, Straus and Giroux. This book was released on 2019-10-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

Uncertainty Theory

Author : Baoding Liu
Publisher : Springer Science & Business Media
ISBN 13 : 3642139582
Total Pages : 350 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Uncertainty Theory by : Baoding Liu

Download or read book Uncertainty Theory written by Baoding Liu and published by Springer Science & Business Media. This book was released on 2011-11-07 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Human Compatible

Author : Stuart Jonathan Russell
Publisher : Penguin Books
ISBN 13 : 0525558616
Total Pages : 354 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis Human Compatible by : Stuart Jonathan Russell

Download or read book Human Compatible written by Stuart Jonathan Russell and published by Penguin Books. This book was released on 2019 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.

Uncertainty in artificial intelligence

Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (136 download)

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Book Synopsis Uncertainty in artificial intelligence by :

Download or read book Uncertainty in artificial intelligence written by and published by . This book was released on 1986 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis

Download Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis PDF Online Free

Author : Carole H. Sudre
Publisher : Springer Nature
ISBN 13 : 3030877353
Total Pages : 306 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis by : Carole H. Sudre

Download or read book Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis written by Carole H. Sudre and published by Springer Nature. This book was released on 2021-09-30 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 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. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period.

Uncertainty in Artificial Intelligence 4

Author : T.S. Levitt
Publisher : Elsevier
ISBN 13 : 1483296547
Total Pages : 422 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Uncertainty in Artificial Intelligence 4 by : T.S. Levitt

Download or read book Uncertainty in Artificial Intelligence 4 written by T.S. Levitt and published by Elsevier. This book was released on 2014-06-28 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clearly illustrated in this volume is the current relationship between Uncertainty and AI. It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally into four sections which highlight both the strengths and weaknesses of the current state of the relationship between Uncertainty and AI.