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The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-volume work covering all major areas of the application of logic to artificial intelligence and logic programming. The authors are chosen on an international basis and are leaders in the fields covered. Volume 5 is the last in this well-regarded series. Logic is now widely recognized as one of the foundational disciplines of computing. It has found applications in virtually all aspects of the subject, from software and hardware engineering to programming languages and artificial intelligence. In response to the growing need for an in-depth survey of these applications the Handbook of Logic in Artificial Intelligence and its companion, the Handbook of Logic in Computer Science have been created. The Handbooks are a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying themes in the various areas. Some mathematical background is assumed, and much of the material will be of interest to logicians and mathematicians. Volume 5 focuses particularly on logic programming. The chapters, which in many cases are of monograph length and scope, emphasize possible unifying themes.
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
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
Perspectives in Computing: A Computational Logic Handbook contains a precise description of the logic and a detailed reference guide to the associated mechanical theorem proving system, including a primer for the logic as a functional programming language, an introduction to proofs in the logic, and a primer for the mechanical theorem. The publication first offers information on a primer for the logic, formalization within the logic, and a precise description of the logic. Discussions focus on induction and recursion, quantification, explicit value terms, dealing with features and omissions, elementary mathematical relationships, Boolean operators, and conventional data structures. The text then takes a look at proving theorems in the logic, mechanized proofs in the logic, and an introduction to the system. The text examines the processes involved in using the theorem prover, four classes of rules generated from lemmas, and aborting or interrupting commands. Topics include executable counterparts, toggle, elimination of irrelevancy, heuristic use of equalities, representation of formulas, type sets, and the crucial check points in a proof attempt. The publication is a vital reference for researchers interested in computational logic.
Highly parallel machines have been available for many years but, because advances in hardware have always outpaced progress in software development, designers and users of these machines have yet to realize their full potential. Until recently there have been few, if any, high-class parallel programming languages that could be implemented on the wide variety of parallel processing systems in use. This book helps to redress the balance by teaching programming techniques as well as performance analysis of parallel programming languages and architectures using logic programming; specifically, it focuses on the Prolog-like languages OR-parallel Prolog and AND-parallel FGHC. Parallel Logic Programmingbrings to light practical applications of a previously esoteric/theoretical area of parallel logic programming and is unique in presenting programming hand-in-hand with performance analysis of real empirical measurements. Its quantitative approach to symbolic parallel programming provides students and professionals with tools for implementing and critically evaluating larger projects. The book includes useful chapter summaries, programming projects, and a glossary.
A one-stop reference, self-contained, with theoretical topics presented in conjunction with implementations for which code is supplied.
The aim of this handbook is to create, for the first time, a systematic account of the field of spatial logic. The book comprises a general introduction, followed by fourteen chapters by invited authors. Each chapter provides a self-contained overview of its topic, describing the principal results obtained to date, explaining the methods used to obtain them, and listing the most important open problems. Jointly, these contributions constitute a comprehensive survey of this rapidly expanding subject.
Description Logics are a family of knowledge representation languages that have been studied extensively in Artificial Intelligence over the last two decades. They are embodied in several knowledge-based systems and are used to develop various real-life applications. The Description Logic Handbook provides a thorough account of the subject, covering all aspects of research in this field, namely: theory, implementation, and applications. Its appeal will be broad, ranging from more theoretically-oriented readers, to those with more practically-oriented interests who need a sound and modern understanding of knowledge representation systems based on Description Logics. The chapters are written by some of the most prominent researchers in the field, introducing the basic technical material before taking the reader to the current state of the subject, and including comprehensive guides to the literature. In sum, the book will serve as a unique reference for the subject, and can also be used for self-study or in conjunction with Knowledge Representation and Artificial Intelligence courses.
The handbook of logic in artificial intelligence and logic programming is an international reference work in five volumes. It has been created in response to the growing need for an in-depth survey of the applications of logic in artifical intelligence. The dramatic increase in research in recent years means that logic is now widely recognised as one of the foundational disciplines of computing and has found applications in virtually all aspects of the subject, from software engineeringand hardware to programming languages and artificial intelligence. Yet this handbook is the first authoritative text to pull together the accumulated research level material, and as such is a unique and invaluable reference source. The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-author multi-volume work covering all the major areas of application of logic to artifical intelligence and logic programming. The Handbook comprises five volumes, each an in-depth overview of one of the major topics in this area. It is the result of years of co-operative effort by internationally renowned researchers in the field, and will no doubt be the standard reference work in artifical intelligence and logic programming for years to come- essential reading for all those interested in this subject. This latest volume covers, among other subjects, epistemic reasoning, time and change for AI, and temporal nonmonotonic reasoning.
The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine and education, including ICAI systems design, intelligent CAI systems, medical systems, and other applications of AI to education. The manuscript explores automatic programming, as well as the methods of program specification, basic approaches, and automatic programming systems. The book is a valuable source of data for computer science experts and researchers interested in conducting further research in artificial intelligence.