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A one-stop reference, self-contained, with theoretical topics presented in conjunction with implementations for which code is supplied.
Book Synopsis Handbook of Practical Logic and Automated Reasoning by : John Harrison
Download or read book Handbook of Practical Logic and Automated Reasoning written by John Harrison and published by Cambridge University Press. This book was released on 2009-03-12 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-stop reference, self-contained, with theoretical topics presented in conjunction with implementations for which code is supplied.
Book Synopsis Handbook of Automated Reasoning by : Alan J.A. Robinson
Download or read book Handbook of Automated Reasoning written by Alan J.A. Robinson and published by Elsevier. This book was released on 2001-06-22 with total page 2128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Automated Reasoning
A comprehensive resource on automated reasoning and its applications.
Book Synopsis Handbook of Automated Reasoning by : J. Alan Robinson
Download or read book Handbook of Automated Reasoning written by J. Alan Robinson and published by MIT Press. This book was released on 2001 with total page 2150 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource on automated reasoning and its applications.
Book Synopsis Handbook of Automated Reasoning by : Alan J.A. Robinson
Download or read book Handbook of Automated Reasoning written by Alan J.A. Robinson and published by Elsevier. This book was released on 2001-06-21 with total page 1198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Automated Reasoning.
Book Synopsis Handbook of Automated Reasoning by : Alan J.A. Robinson
Download or read book Handbook of Automated Reasoning written by Alan J.A. Robinson and published by North Holland. This book was released on 2001-06-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
"Automated scoring engines [...] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have reached maturity, and that there is a growing acceptance of these technologies among experts and the public." From the Foreword by Alina von Davier, ACTNext Senior Vice President Handbook of Automated Scoring: Theory into Practice provides a scientifically grounded overview of the key research efforts required to move automated scoring systems into operational practice. It examines the field of automated scoring from the viewpoint of related scientific fields serving as its foundation, the latest developments of computational methodologies utilized in automated scoring, and several large-scale real-world applications of automated scoring for complex learning and assessment systems. The book is organized into three parts that cover (1) theoretical foundations, (2) operational methodologies, and (3) practical illustrations, each with a commentary. In addition, the handbook includes an introduction and synthesis chapter as well as a cross-chapter glossary.
Book Synopsis Handbook of Automated Scoring by : Duanli Yan
Download or read book Handbook of Automated Scoring written by Duanli Yan and published by CRC Press. This book was released on 2020-02-26 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Automated scoring engines [...] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have reached maturity, and that there is a growing acceptance of these technologies among experts and the public." From the Foreword by Alina von Davier, ACTNext Senior Vice President Handbook of Automated Scoring: Theory into Practice provides a scientifically grounded overview of the key research efforts required to move automated scoring systems into operational practice. It examines the field of automated scoring from the viewpoint of related scientific fields serving as its foundation, the latest developments of computational methodologies utilized in automated scoring, and several large-scale real-world applications of automated scoring for complex learning and assessment systems. The book is organized into three parts that cover (1) theoretical foundations, (2) operational methodologies, and (3) practical illustrations, each with a commentary. In addition, the handbook includes an introduction and synthesis chapter as well as a cross-chapter glossary.
This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence. Key Features: - Broad range: foundations; techniques and applications - Leading researchers around the world have written the chapters - Covers many vital applications - Source book for Artificial Intelligence, temporal reasoning - Approaches provide foundation for many future software systems · Broad range: foundations; techniques and applications · Leading researchers around the world have written the chapters · Covers many vital applications · Source book for Artificial Intelligence, temporal reasoning · Approaches provide foundation for many future software systems
Book Synopsis Handbook of Temporal Reasoning in Artificial Intelligence by : Michael David Fisher
Download or read book Handbook of Temporal Reasoning in Artificial Intelligence written by Michael David Fisher and published by Elsevier. This book was released on 2005-03-01 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection represents the primary reference work for researchers and students in the area of Temporal Reasoning in Artificial Intelligence. Temporal reasoning has a vital role to play in many areas, particularly Artificial Intelligence. Yet, until now, there has been no single volume collecting together the breadth of work in this area. This collection brings together the leading researchers in a range of relevant areas and provides an coherent description of the breadth of activity concerning temporal reasoning in the filed of Artificial Intelligence. Key Features: - Broad range: foundations; techniques and applications - Leading researchers around the world have written the chapters - Covers many vital applications - Source book for Artificial Intelligence, temporal reasoning - Approaches provide foundation for many future software systems · Broad range: foundations; techniques and applications · Leading researchers around the world have written the chapters · Covers many vital applications · Source book for Artificial Intelligence, temporal reasoning · Approaches provide foundation for many future software systems
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 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 1034 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
Interest in computer applications has led to a new attitude to applied logic in which researchers tailor a logic in the same way they define a computer language. In response to this attitude, this text for undergraduate and graduate students discusses major algorithmic methodologies, and tableaux and resolution methods. The authors focus on first-order logic, the use of proof theory, and the computer application of automated searches for proofs of mathematical propositions. Annotation copyrighted by Book News, Inc., Portland, OR
Book Synopsis Proof Theory and Automated Deduction by : Jean Goubault-Larrecq
Download or read book Proof Theory and Automated Deduction written by Jean Goubault-Larrecq and published by Springer Science & Business Media. This book was released on 2001-11-30 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in computer applications has led to a new attitude to applied logic in which researchers tailor a logic in the same way they define a computer language. In response to this attitude, this text for undergraduate and graduate students discusses major algorithmic methodologies, and tableaux and resolution methods. The authors focus on first-order logic, the use of proof theory, and the computer application of automated searches for proofs of mathematical propositions. Annotation copyrighted by Book News, Inc., Portland, OR
Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"
Book Synopsis Handbook of Satisfiability by : A. Biere
Download or read book Handbook of Satisfiability written by A. Biere and published by IOS Press. This book was released on 2021-05-05 with total page 1486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"
