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Author: David W. Etherington
Publisher: Pitman Publishing
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 254
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Book Description
Author: David W. Etherington
Publisher: Pitman Publishing
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 254
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Book Description
Author: Léa Sombé
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 168
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Book Description
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:
Category : Intelligence artificielle
Languages : en
Pages : 472
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Book Description
Author: Torsten Schaub
Publisher: Springer Science & Business Media
ISBN: 9783540645153
Category : Computers
Languages : en
Pages : 180
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Book Description
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: 3030061647
Category : Technology & Engineering
Languages : en
Pages : 808
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Book Description
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: 0080514898
Category : Computers
Languages : en
Pages : 573
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Book Description
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: 9401135347
Category : Computers
Languages : en
Pages : 247
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Book Description
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: Benjamin Kuipers
Publisher: MIT Press
ISBN: 9780262111904
Category : Computers
Languages : en
Pages : 464
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Book Description
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: James Allen
Publisher: Morgan Kaufmann
ISBN:
Category : Computers
Languages : en
Pages : 628
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Book Description
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:
Category : Computers
Languages : en
Pages : 680
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Book Description
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