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| Author | : T.S. Levitt |
| Publisher | : Elsevier |
| Total Pages | : 435 |
| Release | : 2014-06-28 |
| Genre | : Computers |
| ISBN | : 1483296547 |
Download Uncertainty in Artificial Intelligence 4 Book in PDF, ePub and Kindle
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.
| Author | : Max Henrion |
| Publisher | : |
| Total Pages | : 459 |
| Release | : 1990 |
| Genre | : Artificial intelligence |
| ISBN | : 9780444887399 |
Download Uncertainty in Artificial Intelligence 5 Book in PDF, ePub and Kindle
This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty. A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language understanding.
| Author | : Deyi Li |
| Publisher | : CRC Press |
| Total Pages | : 290 |
| Release | : 2017-05-18 |
| Genre | : Mathematics |
| ISBN | : 1498776272 |
Download Artificial Intelligence with Uncertainty Book in PDF, ePub and Kindle
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 | : Khalid Saeed |
| Publisher | : Springer |
| Total Pages | : 541 |
| Release | : 2013-09-20 |
| Genre | : Computers |
| ISBN | : 3642409253 |
Download Computer Information Systems and Industrial Management Book in PDF, ePub and Kindle
This book constitutes the proceedings of the 12th IFIP TC 8 International Conference, CISIM 2013, held in Cracow, Poland, in September 2013. The 44 papers presented in this volume were carefully reviewed and selected from over 60 submissions. They are organized in topical sections on biometric and biomedical applications; pattern recognition and image processing; various aspects of computer security, networking, algorithms, and industrial applications. The book also contains full papers of a keynote speech and the invited talk.
| Author | : Audun Jøsang |
| Publisher | : Springer |
| Total Pages | : 337 |
| Release | : 2016-10-27 |
| Genre | : Computers |
| ISBN | : 3319423371 |
Download Subjective Logic Book in PDF, ePub and Kindle
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.
| Author | : Didier J. Dubois |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 379 |
| Release | : 2014-05-12 |
| Genre | : Computers |
| ISBN | : 1483282872 |
Download Uncertainty in Artificial Intelligence Book in PDF, ePub and Kindle
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 | : Carole H. Sudre |
| Publisher | : Springer Nature |
| Total Pages | : 233 |
| Release | : 2020-10-05 |
| Genre | : Computers |
| ISBN | : 3030603652 |
Download Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis Book in PDF, ePub and Kindle
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 | : David Heckerman |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 554 |
| Release | : 2014-05-12 |
| Genre | : Computers |
| ISBN | : 1483214516 |
Download Uncertainty in Artificial Intelligence Book in PDF, ePub and Kindle
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 | : Bruce D'Ambrosio |
| Publisher | : Elsevier |
| Total Pages | : 445 |
| Release | : 2014-06-28 |
| Genre | : Computers |
| ISBN | : 1483298566 |
Download Uncertainty in Artificial Intelligence Book in PDF, ePub and Kindle
Uncertainty Proceedings 1991
| Author | : Fabio Cuzzolin |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2024-06-05 |
| Genre | : Computers |
| ISBN | : 9783031579622 |
Download Epistemic Uncertainty in Artificial Intelligence Book in PDF, ePub and Kindle
This LNCS 14523 conference volume constitutes the proceedings of the First International Workshop, Epi UAI 2023, in Pittsburgh, PA, USA, August 2023. The 8 full papers together included in this volume were carefully reviewed and selected from 16 submissions. Epistemic AI focuses, in particular, on some of the most important areas of machine learning: unsupervised learning, supervised learning, and reinforcement learning.
