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Author : David W. Etherington
Publisher : Pitman Publishing
ISBN 13 :
Total Pages : 254 pages
Book Rating : 4.:/5 (44 download)
Download or read book Reasoning with Incomplete Information written by David W. Etherington and published by Pitman Publishing. This book was released on 1988 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Léa Sombé
Publisher :
ISBN 13 :
Total Pages : 168 pages
Book Rating : 4.X/5 (1 download)
Download or read book Reasoning Under Incomplete Information In Artificial Intelligence written by Léa Sombé and published by . This book was released on 1990-09-10 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The formalization of ``revisable reasoning'' has been the object of numerous works, developed independently and using many diverse approaches--approaches that are purely symbolic, use numbers to quantify uncertainty, are close to formal logic or less formalized; some deal with exceptions, and a smaller number consider the problem of knowledge bases of revision. This work presents and compares several of these revisable (incomplete) reasoning methods for use in AI. Each method is systematically evaluated with a single example to give the reader an appreciation of the rationale and use of each formulation. The logics considered include: default logic, non-monotonic modal logics, the supposition-based logic, the conditional logics, and the logics of uncertainty. The book also discusses the contribution of works on truth maintenance and logic of action.
Author :
Publisher :
ISBN 13 :
Total Pages : 472 pages
Book Rating : 4.:/5 (222 download)
Download or read book Reasoning Under Incomplete Information in Artificial Intelligence written by and published by . This book was released on 1990 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Torsten Schaub
Publisher : Springer Science & Business Media
ISBN 13 : 9783540645153
Total Pages : 180 pages
Book Rating : 4.6/5 (451 download)
Download or read book The Automation of Reasoning with Incomplete Information written by Torsten Schaub and published by Springer Science & Business Media. This book was released on 1997 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reasoning with incomplete information constitutes a major challenge for any intelligent system. In fact, we expect such systems not to become paralyzed by missing information but rather to arrive at plausible results by bridging the gaps in the information available. A versatile way of reasoning in the absence of information is to reason by default. This book aims at providing formal and practical means for automating reasoning with incomplete information by starting from the approach taken by the framework of default logic. For this endeavor, a bridge is spanned between formal semantics, over systems for default reasoning, to efficient implementation.
Author : Pierre Marquis
Publisher : Springer Nature
ISBN 13 : 3030061647
Total Pages : 808 pages
Book Rating : 4.0/5 (3 download)
Download or read book A Guided Tour of Artificial Intelligence Research written by Pierre Marquis and published by Springer Nature. This book was released on 2020-05-08 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
Author : Judea Pearl
Publisher : Elsevier
ISBN 13 : 0080514898
Total Pages : 573 pages
Book Rating : 4.0/5 (85 download)
Download or read book Probabilistic Reasoning in Intelligent Systems written by Judea Pearl and published by Elsevier. This book was released on 2014-06-28 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Z. Pawlak
Publisher : Springer Science & Business Media
ISBN 13 : 9401135347
Total Pages : 247 pages
Book Rating : 4.4/5 (11 download)
Download or read book Rough Sets written by Z. Pawlak and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of research fields such as Artificial Intelligence and Information Systems. However, the problem is to understand what knowledge means, to find ways of representing knowledge, and to specify automated machineries that can extract useful information from stored knowledge. Knowledge is something people have in their mind, and which they can express through natural language. Knowl edge is acquired not only from books, but also from observations made during experiments; in other words, from data. Changing data into knowledge is not a straightforward task. A set of data is generally disorganized, contains useless details, although it can be incomplete. Knowledge is just the opposite: organized (e.g. laying bare dependencies, or classifications), but expressed by means of a poorer language, i.e. pervaded by imprecision or even vagueness, and assuming a level of granularity. One may say that knowledge is summarized and organized data - at least the kind of knowledge that computers can store.
Author : James Allen
Publisher : Morgan Kaufmann
ISBN 13 :
Total Pages : 628 pages
Book Rating : 4.F/5 ( download)
Download or read book Principles of Knowledge Representation and Reasoning written by James Allen and published by Morgan Kaufmann. This book was released on 1991 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of the Second International Conference on [title] held in Cambridge, Massachusetts, April 1991, comprise 55 papers on topics including the logical specifications of reasoning behaviors and representation formalisms, comparative analysis of competing algorithms and formalisms, and ana
Author : Jon Doyle
Publisher : Morgan Kaufmann
ISBN 13 :
Total Pages : 680 pages
Book Rating : 4.3/5 (91 download)
Download or read book Principles of Knowledge Representation and Reasoning written by Jon Doyle and published by Morgan Kaufmann. This book was released on 1994 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings of KR '94 comprise 55 papers on topics including deduction an search, description logics, theories of knowledge and belief, nonmonotonic reasoning and belief revision, action and time, planning and decision-making and reasoning about the physical world, and the relations between KR
Author : Martin Davis
Publisher : Springer
ISBN 13 : 366248899X
Total Pages : 652 pages
Book Rating : 4.6/5 (624 download)
Download or read book Logic for Programming, Artificial Intelligence, and Reasoning written by Martin Davis and published by Springer. This book was released on 2015-12-01 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 20th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-20, held in November 2015, in Suva, Fiji. The 43 regular papers presented together with 1 invited talk included in this volume were carefully reviewed and selected from 92 submissions. The series of International Conferences on Logic for Programming, Artificial Intelligence and Reasoning, LPAR, is a forum where, year after year, some of the most renowned researchers in the areas of logic, automated reasoning, computational logic, programming languages and their applications come to present cutting-edge results, to discuss advances in these fields, and to exchange ideas in a scientifically emerging part of the world.
Author : Benjamin Kuipers
Publisher : MIT Press
ISBN 13 : 9780262111904
Total Pages : 464 pages
Book Rating : 4.1/5 (119 download)
Download or read book Qualitative Reasoning written by Benjamin Kuipers and published by MIT Press. This book was released on 1994 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model. This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence.
Author : J.C. Bezdek
Publisher : Springer Science & Business Media
ISBN 13 : 1461552435
Total Pages : 527 pages
Book Rating : 4.4/5 (615 download)
Download or read book Fuzzy Sets in Approximate Reasoning and Information Systems written by J.C. Bezdek and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.
Author : Craig MacNish
Publisher : Springer Science & Business Media
ISBN 13 : 9783540583325
Total Pages : 436 pages
Book Rating : 4.5/5 (833 download)
Download or read book Logics in Artificial Intelligence written by Craig MacNish and published by Springer Science & Business Media. This book was released on 1994-08-10 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 1994 European Workshop on Logics in Artificial Intelligence, held at York, UK in September 1994. The 24 papers presented were selected from a total of 79 submissions; in addition there are two abstracts of invited talks and one full paper of the invited presentation by Georg Gottlob. The papers point out that, with the depth and maturity of formalisms and methodologies available in AI today, logics provide a formal basis for the study of the whole field of AI. The volume offers sections on nonmonotonic reasoning, automated reasoning, logic programming, knowledge representation, and belief revision.
Author : Dov M. Gabbay
Publisher : Springer Science & Business Media
ISBN 13 : 9401717338
Total Pages : 446 pages
Book Rating : 4.4/5 (17 download)
Download or read book Abductive Reasoning and Learning written by Dov M. Gabbay and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains leading survey papers on the various aspects of Abduction, both logical and numerical approaches. Abduction is central to all areas of applied reasoning, including artificial intelligence, philosophy of science, machine learning, data mining and decision theory, as well as logic itself.
Author : Didier J. Dubois
Publisher : Morgan Kaufmann
ISBN 13 : 1483282872
Total Pages : 379 pages
Book Rating : 4.4/5 (832 download)
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 : Pierre Marquis
Publisher :
ISBN 13 : 9783030061654
Total Pages : 0 pages
Book Rating : 4.0/5 (616 download)
Download or read book A Guided Tour of Artificial Intelligence Research written by Pierre Marquis and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume.
Author : Michael Clarke
Publisher : Springer Science & Business Media
ISBN 13 : 9783540573951
Total Pages : 408 pages
Book Rating : 4.5/5 (739 download)
Download or read book Symbolic and Quantitative Approaches to Reasoning and Uncertainty written by Michael Clarke and published by Springer Science & Business Media. This book was released on 1993-10-20 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years it has become apparent that an important part of the theory of artificial intelligence is concerned with reasoning on the basis of uncertain, incomplete, or inconsistent information. A variety of formalisms have been developed, including nonmonotonic logic, fuzzy sets, possibility theory, belief functions, and dynamic models of reasoning such as belief revision and Bayesian networks. Several European research projects have been formed in the area and the first European conference was held in 1991. This volume contains the papers accepted for presentation at ECSQARU-93, the European Conference on Symbolicand Quantitative Approaches to Reasoning and Uncertainty, held at the University of Granada, Spain, November 8-10, 1993.
