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About this book
During the last two decades, the idea of Semantic Web has received a great deal of attention. An extensive body of knowledge has emerged to describe technologies that seek to help us create and use aspects of the Semantic Web. Ontology and agent-based technologies are understood to be the two important technologies here. A large number of articles and a number of books exist to describe the use individually of the two technologies and the design of systems that use each of these technologies individually, but little focus has been given on how one can - sign systems that carryout integrated use of the two different technologies. In this book we describe ontology and agent-based systems individually, and highlight advantages of integration of the two different and complementary te- nologies. We also present a methodology that will guide us in the design of the - tegrated ontology-based multi-agent systems and illustrate this methodology on two use cases from the health and software engineering domain. This book is organized as follows: • Chapter I, Current issues and the need for ontologies and agents, describes existing problems associated with uncontrollable information overload and explains how ontologies and agent-based systems can help address these - sues. • Chapter II, Introduction to multi-agent systems, defines agents and their main characteristics and features including mobility, communications and collaboration between different agents. It also presents different types of agents on the basis of classifications done by different authors.
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Keywords
Table of contents (13 chapters)
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Front Matter
Authors and Affiliations
About the authors
Dr Maja Hadzic received PhD from Curtin University of Technology in 2006. Her PhD thesis is entitled: "Ontology-based multi-agent systems for human disease studies". She is currently Research Fellow at the Digital Ecosystems and Business Intelligence Institute of the Curtin University of Technology. She has a multi-disciplinary background and her current research interests include ontologies, multi-agent systems, data mining, digital ecosystems and mental health.
Professor Elizabeth Chang is Professor of Information Systems and Software Engineering at the Curtin University of Technology. She is the Director of the Digital Ecosystems and Business Intelligence Institute. Professor Chang has an extensive background, knowledge and skills in academia, commerce and industry.
Dr Pornpit Wongthongtham received PhD from Curtin University of Technology in 2006 and has become an expert in the field of ontology-based multi-agent systems. Over the last 3 years she co-authored numerous papers on ontology-based multi-agent systems for multi-site software engineering. She is currently working as Research Fellow at the Digital Ecosystems and Business Intelligence Institute of the Curtin University of Technology.
Professor Tharam Dillon is an expert in the field of software engineering, data mining XML based systems, ontologies, trust, security and component-oriented access control. Professor Dillon has published five authored books and four co-edited books. He has also published over 600 scientific papers in refereed journals and conferences. Over the last fifteen years, he has been cited, one or more times, in over 1200 publications. This indicates the high impact of his research work.
Bibliographic Information
Book Title: Ontology-Based Multi-Agent Systems
Authors: Maja Hadzic, Pornpit Wongthongtham, Tharam Dillon, Elizabeth Chang
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-01904-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2009
Hardcover ISBN: 978-3-642-01903-6Published: 25 June 2009
Softcover ISBN: 978-3-642-42549-3Published: 21 September 2014
eBook ISBN: 978-3-642-01904-3Published: 07 July 2009
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIV, 274
Topics: Applications of Mathematics, Mathematical and Computational Engineering, Artificial Intelligence