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Author: Chitta Baral
Publisher: Cambridge University Press
Published: 2003-01-09
Total Pages: 546
ISBN-13: 1139436449
DOWNLOAD EBOOKBaral 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.
Author: Michael Gelfond
Publisher: Cambridge University Press
Published: 2014-03-10
Total Pages: 363
ISBN-13: 1107782872
DOWNLOAD EBOOKKnowledge 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.
Author: Peter Jackson
Publisher: Mit Press
Published: 1989
Total Pages: 255
ISBN-13: 9780262100380
DOWNLOAD EBOOKThis book explores the building of expert systems using logic for knowledge representation and meta-level inference for control. It presents research done by members of the expert systems group of the Department of Artificial Intelligence in Edinburgh, often in collaboration with others, based on two hypotheses: that logic is a suitable knowledge representation language, and that an explicit representation of the control regime of the theorem prover has many advantages. The editors introduce these hypotheses and present the arguments in their favor They then describe Socrates' a tool for the construction of expert systems that is based on these assumptions. They devote the remaining chapters to the solution of problems that arise from the restrictions imposed by Socrates's representation language and from the system's inefficiency. The chapters dealing with the representation problem present a reified approach to temporal logic that makes it possible to use nonstandard logics without extending the system, and describe a general proof method for arbitrary modal logics. Those dealing with the efficiency problem discuss the technique of partial evaluation and its limitations, as well as another possible solution known as assertion-time inference. Peter Jackson is a Senior Scientist in the Department of Applied Mathematics and Computer Sciences at the McDonnell Douglas Research Laboratory in St. Louis. Han Reichgelt is a Lecturer in Department of Psychology at the University of Nottingham. Frank van Harmelen is a Research Fellow in the Mathematical Reasoning Group at the University of Edinburgh.
Author: Luis Moniz Pereira
Publisher: Springer Science & Business Media
Published: 1998-08-26
Total Pages: 266
ISBN-13: 9783540649588
DOWNLOAD EBOOKThis book presents the thoroughly refereed post-workshop proceedings of the Third International Workshop on Logic Programming and Knowledge Representation, LPKR'97, held in Port Jefferson, NY, USA, in October 1997. The eight revised full papers presented have undergone a two-round reviewing process; also included is a comprehensive introduction surveying the state of the art in the area. The volume is divided into topical sections on disjunctive semantics, abduction, priorities, and updates.
Author: Ronald Brachman
Publisher: Morgan Kaufmann
Published: 2004-05-19
Total Pages: 414
ISBN-13: 1558609326
DOWNLOAD EBOOKKnowledge 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.
Author: Pascal Hitzler
Publisher: CRC Press
Published: 2016-04-19
Total Pages: 323
ISBN-13: 1000218724
DOWNLOAD EBOOKCovering the authors' own state-of-the-art research results, this book presents a rigorous, modern account of the mathematical methods and tools required for the semantic analysis of logic programs. It significantly extends the tools and methods from traditional order theory to include nonconventional methods from mathematical analysis that depend on topology, domain theory, generalized distance functions, and associated fixed-point theory. The authors closely examine the interrelationships between various semantics as well as the integration of logic programming and connectionist systems/neural networks.
Author: Frank van Harmelen
Publisher: Elsevier
Published: 2008-01-08
Total Pages: 1035
ISBN-13: 0080557023
DOWNLOAD EBOOKHandbook 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
Author: Marcello Balduccini
Publisher: Springer Science & Business Media
Published: 2011-05-13
Total Pages: 524
ISBN-13: 3642208312
DOWNLOAD EBOOKThis Festschrift volume, published in honor of Michael Gelfond on the occasion of his 65th birthday, contains a collection of papers written by his closest friends and colleagues. Several of these papers were presented during the Symposium on Constructive Mathematics in Computer Science, held in Lexington, KY, USA on October 25-26, 2010. The 27 scientific papers included in the book focus on answer set programming. The papers are organized in sections named “Foundations: ASP and Theories of LP, KR, and NMR”, “ASP and Dynamic Domains”, and “ASP – Applications and Tools”.
Author: Fabrizio Riguzzi
Publisher: CRC Press
Published: 2023-07-07
Total Pages: 548
ISBN-13: 1000923215
DOWNLOAD EBOOKSince its birth, the field of Probabilistic Logic Programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. This book aims at providing an overview of the field with a special emphasis on languages under the Distribution Semantics, one of the most influential approaches. The book presents the main ideas for semantics, inference, and learning and highlights connections between the methods. Many examples of the book include a link to a page of the web application http://cplint.eu where the code can be run online. This 2nd edition aims at reporting the most exciting novelties in the field since the publication of the 1st edition. The semantics for hybrid programs with function symbols was placed on a sound footing. Probabilistic Answer Set Programming gained a lot of interest together with the studies on the complexity of inference. Algorithms for solving the MPE and MAP tasks are now available. Inference for hybrid programs has changed dramatically with the introduction of Weighted Model Integration. With respect to learning, the first approaches for neuro-symbolic integration have appeared together with algorithms for learning the structure for hybrid programs. Moreover, given the cost of learning PLPs, various works proposed language restrictions to speed up learning and improve its scaling.
Author: Michael Kifer
Publisher: ACM Books
Published: 2018-09-19
Total Pages: 615
ISBN-13: 9781970001969
DOWNLOAD EBOOKThe idea of this book grew out of a symposium that was held at Stony Brook in September 2012 in celebration of David S.Warren's fundamental contributions to Computer Science and the area of Logic Programming in particular. Logic Programming (LP) is at the nexus of Knowledge Representation, Artificial Intelligence, Mathematical Logic, Databases, and Programming Languages. It is fascinating and intellectually stimulating due to the fundamental interplay among theory, systems, and applications brought about by logic. Logic programs are more declarative in the sense that they strive to be logical specifications of "what" to do rather than "how" to do it, and thus they are high-level and easier to understand and maintain. Yet, without being given an actual algorithm, LP systems implement the logical specifications automatically. Several books cover the basics of LP but focus mostly on the Prolog language with its incomplete control strategy and non-logical features. At the same time, there is generally a lack of accessible yet comprehensive collections of articles covering the key aspects in declarative LP. These aspects include, among others, well-founded vs. stable model semantics for negation, constraints, object-oriented LP, updates, probabilistic LP, and evaluation methods, including top-down vs. bottom-up, and tabling. For systems, the situation is even less satisfactory, lacking accessible literature that can help train the new crop of developers, practitioners, and researchers. There are a few guides onWarren's Abstract Machine (WAM), which underlies most implementations of Prolog, but very little exists on what is needed for constructing a state-of-the-art declarative LP inference engine. Contrast this with the literature on, say, Compilers, where one can first study a book on the general principles and algorithms and then dive in the particulars of a specific compiler. Such resources greatly facilitate the ability to start making meaningful contributions quickly. There is also a dearth of articles about systems that support truly declarative languages, especially those that tie into first-order logic, mathematical programming, and constraint solving. LP helps solve challenging problems in a wide range of application areas, but in-depth analysis of their connection with LP language abstractions and LP implementation methods is lacking. Also, rare are surveys of challenging application areas of LP, such as Bioinformatics, Natural Language Processing, Verification, and Planning. The goal of this book is to help fill in the previously mentioned void in the LP literature. It offers a number of overviews on key aspects of LP that are suitable for researchers and practitioners as well as graduate students. The following chapters in theory, systems, and applications of LP are included.
