Semantic Networks In Artificial Intelligence
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Principles Of Semantic Networks
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Author : John F. Sowa
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-07-10
Principles Of Semantic Networks written by John F. Sowa and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-10 with Computers categories.
Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.
Semantic Networks In Artificial Intelligence
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Author : Fritz W. Lehmann
language : en
Publisher: Pergamon
Release Date : 1992
Semantic Networks In Artificial Intelligence written by Fritz W. Lehmann and has been published by Pergamon this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Computers categories.
Hardbound. Semantic Networks are graphic structures used to represent concepts and knowledge in computers. Key uses include natural language understanding, information retrieval, machine vision, object-oriented analysis and dynamic control of combat aircraft. This major collection addresses every level of reader interested in the field of knowledge representation. Easy to read surveys of the main research families, most written by the founders, are followed by 25 widely varied articles on semantic networks and the conceptual structure of the world. Some extend ideas of philosopher Charles S Peirce 100 years ahead of his time. Others show connections to databases, lattice theory, semiotics, real-world ontology, graph-grammers, lexicography, relational algebras, property inheritance and semantic primitives. Hundreds of pictures show semantic networks as a visual language of thought.
Principles Of Semantic Networks
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Author : John Sowa
language : en
Publisher:
Release Date : 2014
Principles Of Semantic Networks written by John Sowa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.
Semantic Networks
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Author : Lokendra Shastri
language : en
Publisher: Pitman Publishing
Release Date : 1988
Semantic Networks written by Lokendra Shastri and has been published by Pitman Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
Shastri’s book describes how a high-level specification of hierarchically structured knowledge about concepts and their properties may be encoded as a massively parallel network of a simple processing elements. The evidential formalization of semantic networks leads to a principled treatment of exceptions, multiple inheritance and conflicting information during inheritance, and the best match or partial match computation during recognition. This formalization offers semantically justifiable solutions to a larger class of problems than existing formulations (e.g. default logic). The network operates without the intervention of a central controller or interpreter. The knowledge as well as mechanisms for drawing limited inferences on it are encoded within the network. It uses controlled spreading activation to solve inheritance and recognition problems in time proportional to the depth of the conceptual hierarchy independent of the total number of concepts in the conceptual structure. The number of nodes in the connectionist network is at most quadratic in the number of concepts. The book has six chapters and one appendix. After the introduction in chapter 1 semantic networks their properties and formalizations are discussed in chapter 2. Especially the significance of inheritance and recognition and the evidential approach to it is pointed out here. Chapter 3 specifies a knowledge representation language. The problems of inheritance and recognition are reformulated in this language. In chapter 4 the evidential formalization and its application to inheritance and recognition are demonstrated. Section 4.1 derives an evidence combination rule. In the following two sections this rule is compared to the DEMPSTER-SHAFER evidence combination rule (section 4.2) and to the BAYES’ rule for computing conditional probabilities. The next two sections develop solutions to evidential inheritance (section 4.4) and evidential recognition (section 4.5) together with constraints for a conceptual structure. The connectionist realization of the memory network is developed in chapter 5. First the need for parallelism is discussed (section 5.1), then the connectionist model (section 5.2) and other massively parallel models of semantic memory (section 5.3) are reviewed. The connectionist encoding of the high-level specification is described in section 5.4 together with the connectivity and computational characteristics of node types. This is followed by examples of network encoding (section 5.5) and the elaboration of some implementation details (section 5.6). In section 5.7 and appendix A there is a proof that the proposed network solves the inheritance and recognition problem in accordance with the evidential formulation and in time proportional to the depth of the conceptual hierarchy. Section 5.8 describes the simulation of the proposed system on a conventional computer together with simulation runs of test examples often cited as being problematic. The book ends with a general discussion (chapter 6).
Associative Networks
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Author : Nicholas V. Findler
language : en
Publisher: Academic Press
Release Date : 2014-05-10
Associative Networks written by Nicholas V. Findler and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-10 with Reference categories.
Associative Networks: Representation and Use of Knowledge by Computers is a collection of papers that deals with knowledge base of programs exhibiting some operational aspects of understanding. One paper reviews network formalism that utilizes unobstructed semantics, independent of the domain to which it is applied, that is also capable of handling significant epistemological relationships of concept structuring, attribute/value inheritance, multiple descriptions. Another paper explains network notations that encode taxonomic information; general statements involving quantification; information about processes and procedures; the delineation of local contexts, as well as the relationships between syntactic units and their interpretations. One paper shows that networks can be designed to be intuitively and formally interpretable. Network formalisms are computer-oriented logics which become distinctly significant when access paths from concepts to propositions are built into them. One feature of a topical network organization is its potential for learning. If one topic is too large, it could be broken down where groupings of propositions under the split topics are then based on "co-usage" statistics. As an example, one paper cites the University of Maryland artificial intelligence (AI) group which investigates the control and interaction of a meaning-based parser. The group also analyzes the inferences and predictions from a number of levels based on mundane inferences of actions and causes that can be used in AI. The collection can be useful for computer engineers, computer programmers, mathematicians, and researchers who are working on artificial intelligence.
Introducing Artificial Intelligence
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Author : Geoffrey Leslie Simons
language : en
Publisher: Wiley-Blackwell
Release Date : 1984
Introducing Artificial Intelligence written by Geoffrey Leslie Simons and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Computers categories.
Artificial Intelligence
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Author : Stuart Jonathan Russell
language : en
Publisher: Prentice Hall
Release Date : 2010
Artificial Intelligence written by Stuart Jonathan Russell and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
Artificial intelligence: A Modern Approach, 3e,is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. It is also a valuable resource for computer professionals, linguists, and cognitive scientists interested in artificial intelligence. The revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence.
Human And Artificial Intelligence
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Author : Friedhart Klix
language : en
Publisher: North-Holland
Release Date : 1979
Human And Artificial Intelligence written by Friedhart Klix and has been published by North-Holland this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Computers categories.
Proceedings about the interaction of psychological research and areas in computer--science, especially those covered by artificial intelligence.
Understanding Artificial Intelligence
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Author : Henry C. Mishkoff
language : en
Publisher: Sams Technical Publishing
Release Date : 1988
Understanding Artificial Intelligence written by Henry C. Mishkoff and has been published by Sams Technical Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
Logical Foundations Of Artificial Intelligence
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Author : Michael R. Genesereth
language : en
Publisher: Morgan Kaufmann
Release Date : 1987
Logical Foundations Of Artificial Intelligence written by Michael R. Genesereth and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with COMPUTERS categories.
Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.