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This volume is an attempt to capture the essence of the state-of-the-art of intelligent agent technology and to identify the new challenges and opportunities that it is or will be facing. The most important feature of the volume is that it emphasizes a multi-faceted, holistic view of this emerging technology, from its computational foundations — in terms of models, methodologies, and tools for developing a variety of embodiments of agent-based systems — to its practical impact on tackling real-world problems.
Information Tomorrow offers an engaging, provocative, and wide-ranging discussion for systems librarians, library IT workers, library managers and administrators, and anyone working with or interested in technology in libraries.
This book is a collection of high quality technical papers contributed by active researchers and leading practitioners in intelligent agent technology. It offers a closer look at the state-of-the-art in the development of intelligent agents, and examines in depth the underlying logical, cognitive, physical, and biological foundations as well as the performance characteristics of various approaches in intelligent agent technology. It will stimulate the development of new models, new methodologies, and new tools for building a variety of embodiments of agent-based systems.
This book constitutes the refereed proceedings of the First Asia-Pacific Conference on Web Intelligence, WI 2001, held in Maebashi City, Japan, in October 2001.The 28 revised full papers and 45 revised short papers presented were carefully reviewed and selected from 153 full-length paper submissions. Also included are an introductory survey and six invited presentations. The book offers topical sections on Web information systems environments and foundations, Web human-media engineering, Web information management, Web information retrieval, Web agents, Web mining and farming, and Web-based applications.
Advanced Topics in Database Research features the latest, cutting-edge research findings dealing with all aspects of database management, systems analysis and design and software engineering. This book provides information that is instrumental in the improvement and development of theory and practice related to information technology and management of information resources.
This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being. This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches. We are proud to offer the readers this book.
A diverse international set of authors discuss Artificial/Computational Sapience and Sapient Systems in this unique and useful volume. The reader is guided through the subject in a structured and comprehensive manner that begins with chapters discussing philosophical, historical, and semiotic ideas about what properties are expected from Sapient (Wise) systems. Following that, chapters describe mathematical and engineering views on sapience, relating these to philosophical, semiotic, cognitive, and neuro-biological perspectives.
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
The field of Artificial Intelligence in Education has continued to broaden and now includes research and researchers from many areas of technology and social science. This study opens opportunities for the cross-fertilization of information and ideas from researchers in the many fields that make up this interdisciplinary research area, including artificial intelligence, other areas of computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which Artificial Intelligence in Education systems have been designed and built. An explicit goal is to appeal to those researchers who share the perspective that true progress in learning technology requires both deep insight into technology and also deep insight into learners, learning, and the context of learning. The theme reflects this basic duality.