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
'While there is growing recognition that understanding knowledge is at the very heart of economics, little work has thus far been forthcoming representing in a comprehensive and coherent way its fundamental nature and wide-ranging consequences for economic analysis. The editors are to be commended for having filled this critical gap by providing a well-organized collection of outstanding contributions. This rich and greatly needed Handbook is comprised of contributions about the role knowledge plays in the history of the discipline as well as the most significant current developments as we witness them, particularly in the branches of evolutionary, institutional and complexity economics.' – Kurt Dopfer, University of St Gallen, Switzerland Why do societies benefit differently from knowledge? How exactly does social interaction interfere with knowledge acquisition and diffusion? This original Handbook brings together a wide range of differing approaches to shed light on these questions and others relating to the role and relevance of knowledge in economic analysis. By illuminating the philosophical roots of the various notions of knowledge employed by economists, this Handbook helps to disentangle conceptual and typological issues surrounding the debate on knowledge among economists. Wide-ranging in scope, it explores fundamental aspects of the relationship between knowledge and economics – such as the nature of knowledge, knowledge acquisition and knowledge diffusion. This important compendium embraces various fields and traditions of economic analysis and discusses the role of knowledge in 21 papers from outstanding international scholars. Advanced scholars and postgraduate students interested in cross-fertilization between different fields of economic analysis will find this Handbook of considerable importance.
The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.
This new handbook, with contributions from experts around the world, is the most comprehensive treatise on work design and job analysis practice and research in over 20 years. The handbook, dedicated to Sidney Gael, is the next generation of Gael’s successful Job Analysis Handbook for Business, Industry and Government, published by Wiley in 1988. It consists of four parts: Methods, Systems, Applications and Research/Innovations. Finally, a tightly integrated, user-friendly handbook, of interest to students, practitioners and researchers in the field of Industrial Organizational Psychology and Human Resource Management. Sample Chapter available: Chapter 24, Training Needs Assessment by Eric A. Surface is available for download.
Sponsored by Division 15 of APA, the second edition of this groundbreaking book has been expanded to 41 chapters that provide unparalleled coverage of this far-ranging field. Internationally recognized scholars contribute up-to-date reviews and critical syntheses of the following areas: foundations and the future of educational psychology, learners’ development, individual differences, cognition, motivation, content area teaching, socio-cultural perspectives on teaching and learning, teachers and teaching, instructional design, teacher assessment, and modern perspectives on research methodologies, data, and data analysis. New chapters cover topics such as adult development, self-regulation, changes in knowledge and beliefs, and writing. Expanded treatment has been given to cognition, motivation, and new methodologies for gathering and analyzing data. The Handbook of Educational Psychology, Second Edition provides an indispensable reference volume for scholars, teacher educators, in-service practitioners, policy makers and the academic libraries serving these audiences. It is also appropriate for graduate level courses devoted to the study of educational psychology.
Our homes anticipate when we want to wake up. Our computers predict what music we want to buy. Our cars adapt to the way we drive. In today’s world, even washing machines, rice cookers and toys have the capability of autonomous decision-making. As we grow accustomed to computing power embedded in our surroundings, it becomes clear that these ‘smart environments’, with a number of devices controlled by a coordinating system capable of ‘ambient intelligence’, will play an ever larger role in our lives. This handbook provides readers with comprehensive, up-to-date coverage in what is a key technological field. . Systematically dealing with each aspect of ambient intelligence and smart environments, the text covers everything, from visual information capture and human/computer interaction to multi-agent systems, network use of sensor data, and building more rationality into artificial systems. The book also details a wide range of applications, examines case studies of recent major projects from around the world, and analyzes both the likely impact of the technology on our lives, and its ethical implications. With a wide variety of separate disciplines all conducting research relevant to this field, this handbook encourages collaboration between disparate researchers by setting out the fundamental concepts from each area that are relevant to ambient intelligence and smart environments, providing a fertile soil in which ground-breaking new work candevelop.
Includes established theories and cutting-edge developments. Presents the work of an international group of experts. Presents the nature, origin, implications, an future course of major unresolved issues in the area.
The Handbook of Artificial Intelligence, Volume I focuses on the progress in artificial intelligence (AI) and its increasing applications, including parsing, grammars, and search methods. The book first elaborates on AI, AI handbook and literature, problem representation, search methods, and sample search programs. The text then ponders on representation of knowledge, including survey of representation techniques and representation schemes. The manuscript explores understanding natural languages, as well as machine translation, grammars, parsing, test generation, and natural language processing systems. The book also takes a look at understanding spoken language, including systems architecture and the ARPA SUR projects. The text is a valuable source of information for computer science experts and researchers interested in pursuing further research in artificial intelligence