Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Knowledge Representation And Reasoning
Download Knowledge Representation And Reasoning full books in PDF, epub, and Kindle. Read online Knowledge Representation And Reasoning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Knowledge Representation and Reasoning by : Ronald Brachman
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 Synopsis Knowledge Representation, Reasoning, and the Design of Intelligent Agents by : Michael Gelfond
Download or read book Knowledge Representation, Reasoning, and the Design of Intelligent Agents written by Michael Gelfond and published by Cambridge University Press. This book was released on 2014-03-10 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming (ASP) and action languages, this book shows how knowledge-intensive systems can be given knowledge about the world and how it can be used to solve non-trivial computational problems. The authors maintain a balance between mathematical analysis and practical design of intelligent agents. All the concepts, such as answering queries, planning, diagnostics, and probabilistic reasoning, are illustrated by programs of ASP. The text can be used for AI-related undergraduate and graduate classes and by researchers who would like to learn more about ASP and knowledge representation.
Book Synopsis Knowledge Representation, Reasoning and Declarative Problem Solving by : Chitta Baral
Download or read book Knowledge Representation, Reasoning and Declarative Problem Solving written by Chitta Baral and published by Cambridge University Press. This book was released on 2003-01-09 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Baral shows how to write programs that behave intelligently, by giving them the ability to express knowledge and to reason. This book will appeal to practising and would-be knowledge engineers wishing to learn more about the subject in courses or through self-teaching.
Book Synopsis Principles of Knowledge Representation and Reasoning by : Jon Doyle
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
Book Synopsis Handbook of Knowledge Representation by : Frank van Harmelen
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 Synopsis Foundations of Knowledge Representation and Reasoning by : Gerhard Lakemeyer
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 Synopsis Graph-based Knowledge Representation by : Michel Chein
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 Synopsis Graph Structures for Knowledge Representation and Reasoning by : Michael Cochez
Download or read book Graph Structures for Knowledge Representation and Reasoning written by Michael Cochez and published by Springer Nature. This book was released on 2021-04-16 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes the thoroughly refereed post-conference proceedings of the 6th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence. The 7 revised full papers presented together with 2 invited contributions were reviewed and selected from 9 submissions. The contributions address various issues for knowledge representation and reasoning and the common graph-theoretic background, which allows to bridge the gap between the different communities.
Book Synopsis Reasoning About Knowledge by : Ronald Fagin
Download or read book Reasoning About Knowledge written by Ronald Fagin and published by MIT Press. This book was released on 2004-01-09 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reasoning about knowledge—particularly the knowledge of agents who reason about the world and each other's knowledge—was once the exclusive province of philosophers and puzzle solvers. More recently, this type of reasoning has been shown to play a key role in a surprising number of contexts, from understanding conversations to the analysis of distributed computer algorithms. Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed systems, artificial intelligence, and game theory. It brings eight years of work by the authors into a cohesive framework for understanding and analyzing reasoning about knowledge that is intuitive, mathematically well founded, useful in practice, and widely applicable. The book is almost completely self-contained and should be accessible to readers in a variety of disciplines, including computer science, artificial intelligence, linguistics, philosophy, cognitive science, and game theory. Each chapter includes exercises and bibliographic notes.
Book Synopsis Principles of Semantic Networks by : John F. Sowa
Download or read book Principles of Semantic Networks written by John F. Sowa and published by Morgan Kaufmann. This book was released on 2014-07-10 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Representing and Reasoning with Probabilistic Knowledge by : Fahiem Bacchus
Download or read book Representing and Reasoning with Probabilistic Knowledge written by Fahiem Bacchus and published by Cambridge, Mass. : MIT Press. This book was released on 1990 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic information has many uses in an intelligent system. This book explores logical formalisms for representing and reasoning with probabilistic information that will be of particular value to researchers in nonmonotonic reasoning, applications of probabilities, and knowledge representation. It demonstrates that probabilities are not limited to particular applications, like expert systems; they have an important role to play in the formal design and specification of intelligent systems in general. Fahiem Bacchus focuses on two distinct notions of probabilities: one propositional, involving degrees of belief, the other proportional, involving statistics. He constructs distinct logics with different semantics for each type of probability that are a significant advance in the formal tools available for representing and reasoning with probabilities. These logics can represent an extensive variety of qualitative assertions, eliminating requirements for exact point-valued probabilities, and they can represent firstshy;order logical information. The logics also have proof theories which give a formal specification for a class of reasoning that subsumes and integrates most of the probabilistic reasoning schemes so far developed in AI. Using the new logical tools to connect statistical with propositional probability, Bacchus also proposes a system of direct inference in which degrees of belief can be inferred from statistical knowledge and demonstrates how this mechanism can be applied to yield a powerful and intuitively satisfying system of defeasible or default reasoning. Fahiem Bacchus is Assistant Professor of Computer Science at the University of Waterloo, Ontario. Contents: Introduction. Propositional Probabilities. Statistical Probabilities. Combining Statistical and Propositional Probabilities Default Inferences from Statistical Knowledge.
Book Synopsis Qualitative Reasoning by : Benjamin Kuipers
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.
Book Synopsis Fundamentals of Artificial Intelligence by : K.R. Chowdhary
Download or read book Fundamentals of Artificial Intelligence written by K.R. Chowdhary and published by Springer Nature. This book was released on 2020-04-04 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Book Synopsis Artificial Intelligence: A New Synthesis by : Nils J. Nilsson
Download or read book Artificial Intelligence: A New Synthesis written by Nils J. Nilsson and published by Elsevier. This book was released on 1998-04-17 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches. - An evolutionary approach provides a unifying theme - Thorough coverage of important AI ideas, old and new - Frequent use of examples and illustrative diagrams - Extensive coverage of machine learning methods throughout the text - Citations to over 500 references - Comprehensive index
Book Synopsis Natural Language Processing and Knowledge Representation by : Łucja M. Iwańska
Download or read book Natural Language Processing and Knowledge Representation written by Łucja M. Iwańska and published by AAAI Press. This book was released on 2000-06-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.
Download or read book Vivid Logic written by Gerd Wagner and published by Springer. This book was released on 1994 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Knowledge representation research is not only formal, it is also descriptiveand normative. Its aim is to implement a formal system which captures a practically relevant body of cognitive faculties employed by humans and capitalizes on its technical strength to extend human knowledge representation and reasoning capabilities. In this monograph, the author develops formalisms for his own notion of a vivid knowledge representation and reasoning system, characterized by the presence of two kinds of negation (weak and strong) and the requirements of restricted reflexivity, constructivity, and non-explosiveness. The book is based on work carried out within an interdisciplinary research project at the Free University of Berlin."--PUBLISHER'S WEBSITE.
Book Synopsis Codeless Data Structures and Algorithms by : Armstrong Subero
Download or read book Codeless Data Structures and Algorithms written by Armstrong Subero and published by Apress. This book was released on 2020-02-13 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of self-taught developers and programmers, essential topics in the industry are frequently learned without a formal academic foundation. A solid grasp of data structures and algorithms (DSA) is imperative for anyone looking to do professional software development and engineering, but classes in the subject can be dry or spend too much time on theory and unnecessary readings. Regardless of your programming language background, Codeless Data Structures and Algorithms has you covered. In this book, author Armstrong Subero will help you learn DSAs without writing a single line of code. Straightforward explanations and diagrams give you a confident handle on the topic while ensuring you never have to open your code editor, use a compiler, or look at an integrated development environment. Subero introduces you to linear, tree, and hash data structures and gives you important insights behind the most common algorithms that you can directly apply to your own programs. Codeless Data Structures and Algorithms provides you with the knowledge about DSAs that you will need in the professional programming world, without using any complex mathematics or irrelevant information. Whether you are a new developer seeking a basic understanding of the subject or a decision-maker wanting a grasp of algorithms to apply to your projects, this book belongs on your shelf. Quite often, a new, refreshing, and unpretentious approach to a topic is all you need to get inspired. What You'll LearnUnderstand tree data structures without delving into unnecessary details or going into too much theoryGet started learning linear data structures with a basic discussion on computer memory Study an overview of arrays, linked lists, stacks and queues Who This Book Is ForThis book is for beginners, self-taught developers and programmers, and anyone who wants to understand data structures and algorithms but don’t want to wade through unnecessary details about quirks of a programming language or don’t have time to sit and read a massive book on the subject. This book is also useful for non-technical decision-makers who are curious about how algorithms work.
