Uncertainty And Artificial Intelligence
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Artificial Intelligence With Uncertainty
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Author : Deyi Li
language : en
Publisher: CRC Press
Release Date : 2017-05-18
Artificial Intelligence With Uncertainty written by Deyi Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-18 with Mathematics categories.
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 And Artificial Intelligence
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Author : Abdelkhalak El Hami
language : en
Publisher: John Wiley & Sons
Release Date : 2024-01-04
Uncertainty And Artificial Intelligence written by Abdelkhalak El Hami and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-04 with Computers categories.
Today's information technology, along with Artificial Intelligence (AI), is moving towards total communication between all computerized systems. AI is a representation of human intelligence based on the creation and application of algorithms in specific computer environments. Its aim is to enable computers to act like human beings. For it to work, this type of technology requires computer systems, data with management systems and advanced algorithms, used by AI. In mechanical engineering, AI can offer many possibilities: in mechanical construction, predictive maintenance, plant monitoring, robotics, additive manufacturing, materials, vibration control and agro composites, among many others. This book is dedicated to Artificial Intelligence uncertainties in mechanical problems. Each chapter clearly sets out used and developed illustrative examples. Aimed at students, Uncertainty and Artificial Intelligence is also a valuable resource for practicing engineers and research lecturers.
Uncertainty In Artificial Intelligence
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Author : Prakash P. Shenoy
language : en
Publisher: Morgan Kaufmann Publishers
Release Date : 1998
Uncertainty In Artificial Intelligence written by Prakash P. Shenoy and has been published by Morgan Kaufmann Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
Uncertainty In Artificial Intelligence
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Author : MKP
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Uncertainty In Artificial Intelligence written by MKP 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.
Uncertainty Proceedings 1994
Uncertainty In Artificial Intelligence
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Author : David Heckerman
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-05-12
Uncertainty In Artificial Intelligence written by David Heckerman and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Computers categories.
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 In Artificial Intelligence
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Author : Didier J. Dubois
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-05-12
Uncertainty In Artificial Intelligence written by Didier J. Dubois and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-12 with Computers categories.
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.
Uncertainty In Artificial Intelligence
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Author : L.N. Kanal
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Uncertainty In Artificial Intelligence written by L.N. Kanal 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.
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.
Uncertainty In Artificial Intelligence
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Author : Bruce D'Ambrosio
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Uncertainty In Artificial Intelligence written by Bruce D'Ambrosio 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.
Uncertainty Proceedings 1991
Uncertainty In Artificial Intelligence 4
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Author : T.S. Levitt
language : en
Publisher: Elsevier
Release Date : 2014-06-28
Uncertainty In Artificial Intelligence 4 written by T.S. Levitt 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.
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.