Knowledge Representation, Reasoning and Declarative Problem Solving

Knowledge Representation, Reasoning and Declarative Problem Solving

Author: Chitta Baral

Publisher: Cambridge University Press

Published: 2003-01-09

Total Pages: 546

ISBN-13: 1139436449

DOWNLOAD EBOOK

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.


Knowledge Representation, Reasoning, and the Design of Intelligent Agents

Knowledge Representation, Reasoning, and the Design of Intelligent Agents

Author: Michael Gelfond

Publisher: Cambridge University Press

Published: 2014-03-10

Total Pages: 363

ISBN-13: 1107782872

DOWNLOAD EBOOK

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.


Logic-based Knowledge Representation

Logic-based Knowledge Representation

Author: Peter Jackson

Publisher: Mit Press

Published: 1989

Total Pages: 255

ISBN-13: 9780262100380

DOWNLOAD EBOOK

This 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.


Logic Programming and Knowledge Representation

Logic Programming and Knowledge Representation

Author: Luis Moniz Pereira

Publisher: Springer Science & Business Media

Published: 1998-08-26

Total Pages: 266

ISBN-13: 9783540649588

DOWNLOAD EBOOK

This 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.


Knowledge Representation and Reasoning

Knowledge Representation and Reasoning

Author: Ronald Brachman

Publisher: Morgan Kaufmann

Published: 2004-05-19

Total Pages: 414

ISBN-13: 1558609326

DOWNLOAD EBOOK

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.


Mathematical Aspects of Logic Programming Semantics

Mathematical Aspects of Logic Programming Semantics

Author: Pascal Hitzler

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 323

ISBN-13: 1000218724

DOWNLOAD EBOOK

Covering 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.


Handbook of Knowledge Representation

Handbook of Knowledge Representation

Author: Frank van Harmelen

Publisher: Elsevier

Published: 2008-01-08

Total Pages: 1035

ISBN-13: 0080557023

DOWNLOAD EBOOK

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


Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning

Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning

Author: Marcello Balduccini

Publisher: Springer Science & Business Media

Published: 2011-05-13

Total Pages: 524

ISBN-13: 3642208312

DOWNLOAD EBOOK

This 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”.


Foundations of Probabilistic Logic Programming

Foundations of Probabilistic Logic Programming

Author: Fabrizio Riguzzi

Publisher: CRC Press

Published: 2023-07-07

Total Pages: 548

ISBN-13: 1000923215

DOWNLOAD EBOOK

Since 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.


The Handbook On Reasoning-based Intelligent Systems

The Handbook On Reasoning-based Intelligent Systems

Author: Kazumi Nakamatsu

Publisher: World Scientific

Published: 2013-01-18

Total Pages: 680

ISBN-13: 9814489166

DOWNLOAD EBOOK

This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.