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Book Information Theory  Inference and Learning Algorithms

Download or read book Information Theory Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Book Knowledge Representation and Reasoning Under Uncertainty

Download or read book Knowledge Representation and Reasoning Under Uncertainty written by Michael Masuch and published by Springer Science & Business Media. This book was released on 1994-06-28 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on the International Conference Logic at Work, held in Amsterdam, The Netherlands, in December 1992. The 14 papers in this volume are selected from 86 submissions and 8 invited contributions and are all devoted to knowledge representation and reasoning under uncertainty, which are core issues of formal artificial intelligence. Nowadays, logic is not any longer mainly associated to mathematical and philosophical problems. The term applied logic has a far wider meaning, as numerous applications of logical methods, particularly in computer science, artificial intelligence, or formal linguistics, testify. As demonstrated also in this volume, a variety of non-standard logics gained increased importance for knowledge representation and reasoning under uncertainty.

Book Foundations of Knowledge Representation and Reasoning

Download or read book Foundations of Knowledge Representation and Reasoning written by Gerhard Lakemeyer and published by Springer Science & Business Media. This book was released on 1994-06-28 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers collected in this book cover a wide range of topics in asymptotic statistics. In particular up-to-date-information is presented in detection of systematic changes, in series of observation, in robust regression analysis, in numerical empirical processes and in related areas of actuarial sciences and mathematical programming. The emphasis is on theoretical contributions with impact on statistical methods employed in the analysis of experiments and observations by biometricians, econometricians and engineers.

Book Principles of Knowledge Representation and Reasoning

Download or read book Principles of Knowledge Representation and Reasoning written by Bernhard Nebel and published by Morgan Kaufmann Publishers. This book was released on 1992 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stringently reviewed papers presented at the October 1992 meeting held in Cambridge, Mass., address such topics as nonmonotonic logic; taxonomic logic; specialized algorithms for temporal, spatial, and numerical reasoning; and knowledge representation issues in planning, diagnosis, and natural langu

Book Knowledge Representation and Organization in Machine Learning

Download or read book Knowledge Representation and Organization in Machine Learning written by Katharina Morik and published by . This book was released on 1989 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become a rapidly growing field of Artificial Intelligence. Since the First International Workshop on Machine Learning in 1980, the number of scientists working in the field has been increasing steadily. This situation allows for specialization within the field. There are two types of specialization: on subfields or, orthogonal to them, on special subjects of interest. This book follows the thematic orientation. It contains research papers, each of which throws light upon the relation between knowledge representation, knowledge acquisition and machine learning from a different angle. Building up appropriate representations is considered to be the main concern of knowledge acquisition for knowledge-based systems throughout the book. Here machine learning is presented as a tool for building up such representations. But machine learning itself also states new representational problems. This book gives an easy-to-understand insight into a new field with its problems and the solutions it offers. Thus it will be of good use to both experts and newcomers to the subject.

Book Graph based Knowledge Representation

Download or read book Graph based Knowledge Representation written by Michel Chein and published by Springer Science & Business Media. This book was released on 2008-10-20 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmicqualitiesofgraphshavelongbeenstudied,asindatabasesandconstraint networks.

Book Principles of Knowledge Representation and Reasoning

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

Book Knowledge Representation and Defeasible Reasoning

Download or read book Knowledge Representation and Defeasible Reasoning written by Henry E. Kyburg Jr. and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) ani mal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psy chology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelli gence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also ap pear from time to time. The present volume provides a collection of studies that focus on some of the central problems within the domain of artificial intelligence. These difficulties fall into four principal areas: defeasible reasoning (including the frame problem as apart), ordinary language (and the representation prob lems that it generates), the revision of beliefs (and its rules of inference), and knowledge representation (and the logical problems that are encountered there). These papers make original contributions to each of these areas of inquiry and should be of special interest to those who understand the crucial role that is played by questions of logical form. They vividly illustrate the benefits that can emerge from collaborative efforts involving scholars from linguistics, philosophy, computer science, and AI. J. H. F.

Book Readings in Knowledge Representation

Download or read book Readings in Knowledge Representation written by Ronald J. Brachman and published by Morgan Kaufmann Publishers. This book was released on 1985 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Artificial Intelligence, it is often said that the representation of knowledge is the key to the design of robust intelligent systems. In one form or another the principles of Knowledge Representation are fundamental to work in natural language processing, computer vision, knowledge-based expert systems, and other areas. The papers reprinted in this volume have been collected to allow the reader with a general technical background in AI to explore the subtleties of this key subarea. These seminal articles, spanning a quarter-century of research, cover the most important ideas and developments in the representation field. The editors introduce each paper, discuss its relevance and context, and provide an extensive bibliography of other work. "Readings in Knowledge Representation" is intended to serve as a complete sourcebook for the study of this crucial subject.

Book Handbook of Knowledge Representation

Download or read book Handbook of Knowledge Representation written by Frank van Harmelen and published by Elsevier. This book was released on 2008-01-08 with total page 1035 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily

Book Knowledge Representation and Metaphor

Download or read book Knowledge Representation and Metaphor written by E. Cornell Way and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F.

Book Knowledge Representation

Download or read book Knowledge Representation written by Han Reichgelt and published by Intellect (UK). This book was released on 1991 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most researchers to date in artificial intelligence has been based on the knowledge representation hypothesis, that is, the assumption that in any artificial intelligence (AI) programme there is a separate module which represents the information that the programme has about the world. As a result, a number of so-called knowlege representation formalisms have been developed for representing this kind of information in a computer.

Book Knowledge Representation and Reasoning

Download or read book Knowledge Representation and Reasoning written by Ronald Brachman and published by Morgan Kaufmann. This book was released on 2004-05-19 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.

Book Information Modelling and Knowledge Bases III

Download or read book Information Modelling and Knowledge Bases III written by Setsuo Ohsuga and published by IOS Press. This book was released on 1992 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers direct the focus of interest to the development and use of conceptual models in information systems of various kinds and aim at improving awareness about general or specific problems and solutions in conceptual modelling.

Book Knowledge Representation for Agents and Multi Agent Systems

Download or read book Knowledge Representation for Agents and Multi Agent Systems written by John-Jules Meyer and published by Springer Science & Business Media. This book was released on 2009-10-26 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Knowledge Representation for Agents and Multi-Agent Systems, KRAMAS 2008, held in Sydney, Australia, in September 2008 as a satellite event of KR 2008, the 11th International Conference on Principles of Knowledge Representation and Reasoning. The 10 revised full papers presented were carefully reviewed and selected from 14 submissions. The papers foster the cross-fertilization between the KR (knowledge representation and reasoning) and agent communities, by discussing knowledge representation theories and techniques for agent-based systems.

Book Knowledge in Formation

    Book Details:
  • Author : Janos J. Sarbo
  • Publisher : Springer Science & Business Media
  • Release : 2011-06-16
  • ISBN : 3642170897
  • Pages : 219 pages

Download or read book Knowledge in Formation written by Janos J. Sarbo and published by Springer Science & Business Media. This book was released on 2011-06-16 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Humans have an extraordinary capability to combine different types of information in a single meaningful interpretation. The quickness with which interpretation processes evolve suggests the existence of a uniform procedure for all domains. In this book the authors suggest that such a procedure can be found. They concentrate on the introduction of a theory of interpretation, and they define a model that enables a meaningful representation of knowledge, based on a dynamic view of information and a cognitive model of human information processing. The book consists of three parts. The first part focuses on the properties of signs and sign interpretation; in the second part the authors introduce a model that complies with the conditions for sign processing set by the first part; and in the third part they examine applications of their model in the domain of logic, natural language, reasoning and mathematics. Finally they show how these domains pop up as perspectives in an overall model of knowledge representation. The reader is assumed to have some interest in human information processing and knowledge modeling. Natural language is considered in the obvious sense, familiarity with linguistic theories is not required. Sign theoretical concepts are restricted to a manageable subset, which is introduced gently. Finally, some familiarity with basic concepts of propositional and syllogistic logic may be useful.

Book Part Whole Reasoning in an Object Centered Framework

Download or read book Part Whole Reasoning in an Object Centered Framework written by Patrick Lambrix and published by Springer. This book was released on 2003-06-29 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the author develops an object-centered framework with specialized support of the part-of relation based on description logics. These logics are a family of object-centered knowledge representation languages tailored for describing knowledge about concepts and is-a hierarchies of these concepts. In addition to the representation and reasoning facilities provided by description logics for is-a, representation and reasoning facilities are introduced for part-of. Finally, the feasibility and the usefulness of the approach is demonstrated by applying the framework to various areas including domain modeling, agent-oriented scenarios, document management and retrieval, and composite concept learning.