Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

Indexed In: SCOPUS
Release Date: December, 2008|Copyright: © 2009 |Pages: 450
DOI: 10.4018/978-1-60566-144-5
ISBN13: 9781605661445|ISBN10: 1605661449|EISBN13: 9781605661452
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Description & Coverage
Description:

Cutting-edge developments in artificial intelligence are now driving applications that are only hinting at the level of value they will soon contribute to organizations, consumers, and societies across all domains.

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications offers an enriched set of research articles in artificial intelligence (AI), covering significant AI subjects such as information retrieval, conceptual modeling, supply chain demand forecasting, and machine learning algorithms. This comprehensive collection provides libraries with a one-stop resource to equip the academic, industrial, and managerial communities with an in-depth look into the most pertinent AI advances that will lead to the most valuable applications.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Active information systems
  • Artificial Intelligence
  • Automatic Web page organization
  • Causal strategy models
  • Conceptual Modeling
  • Demand supply network optimization
  • Empirical inference of numerical information
  • E-trade auction
  • Forecasting supply chain demand
  • Information modeling
  • Information Retrieval
  • Knowledge acquisition process
  • Knowledge-driven decision support
  • Logic specifications
  • Machine Learning Algorithms
  • Multi-agent architecture
  • Multi-Agent Systems
  • Petri Nets
  • Problem of universals
  • Rough Set Theory
  • Search engine performance comparisons
  • Trust formalization
  • Web Mining
Reviews & Statements

This book discusses a number of agent based applications developed for knowledge-driven decision support, online auctions, federated information systems, and mobile computing. Similarly, in the area of search and retrieval, the book provides current research in search engine performance, user centered approach for information and image retrieval, web mining and document clustering.

– Vijayan Sugumaran, Oakland University, USA

Research from around the world, collected here, examines a number of agent-based applications developed for knowledge-driven decision support, online auctions, federal information systems, and mobile computing.

– Book News Inc. (March 2009)
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Editor/Author Biographies
Vijayan Sugumaran is Distinguished Professor of Management Information Systems and Chair of the Decision and Information Sciences department at Oakland University. He is also Co-Director of the Center for Data Science and Big Data Analytics at Oakland University. He received his Ph.D. in Information Technology from George Mason University, Fairfax, Virginia, USA. Over the years he has taught courses at the Graduate and Undergraduate level in Object-Oriented Systems Development, C++, Java, Javascript, Database Management Systems and Data Warehouses, Advanced Databases and Big Data Management, Deep Learning and Text Analytics, Systems Analysis and Design, Electronic Commerce, and Introduction to MIS. His research interests are in the areas of Big Data Analytics, Business Intelligence, Ontologies and Semantic Web, Intelligent Agent and Multi-Agent Systems, Component Based Software Development, Knowledge-Based Systems, and Data & Information Modeling. He has published over 275 peer-reviewed articles in Journals, Conferences, and Books. He has edited twenty books. His recent publications have appeared in Information Systems Research, ACM Transactions on Database Systems, IEEE Transactions on Engineering Management, IEEE Transactions on Big Data, IEEE Transactions on Education, IEEE software, Communications of the ACM, Healthcare Management Science, Data and Knowledge Engineering, The DATABASE for Advances in Information Systems, Information Systems Journal, and Journal of Information Systems and E-Business Management. He is also the editor-in-chief of the International Journal of Intelligent Information Technologies and also serves on the editorial board of eight other journals. He was the Program Co-Chair for the International Conference on Applications of Natural Language to Information Systems (NLDB 2008, NLDB 2013, NLDB 2016, NLDB 2019, and NLDB 2023). He was also the Chair of Intelligent Information Systems track for the Information Resources Management Association International Conference (IRMA 2001, 2002, 2005 - 2007) and the Intelligent Agent and Multi-Agent Systems in Business mini-track for Americas Conference on Information Systems (AMCIS 1999 - 2023). He served as Program Co-Chair for the 14th Workshop on E-Business (WeB2015), 29th Australasian Conference on Information Systems (ACIS 2018), 14th Annual Conference of Midwest Association for Information Systems (MWAIS 2019), 5th IEEE International Conference on Big Data Service and Applications (BDS 2019), and 2022 Midwest Decision Sciences Institute Annual Conference (MWDSI 2022). He also served as Chair of the E-Commerce track for Decision Science Institute’s Annual Conference, 2004. He was the Information Technology Coordinator for the Decision Sciences Institute from 2007 to 2010. He also regularly serves as a program committee member for numerous national and international conferences.
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Editorial Advisory Board
  • Akhilesh Bajaj, University of Tulsa, USA
  • Ralph Bergmann, University of Trier, Germany
  • Kaushal Chari, University of South Florida, USA
  • Roger Chiang, University of Cincinnati, USA
  • Dursun Delen, Oklahoma State University, USA
  • Armin Heinzl, University of Mannheim, Germany
  • Dawn Jutla, Saint Mary's University, Canada
  • Rajiv Kishore, SUNY at Buffalo, USA
  • Christoph Schlueter Langdon, University of Southern California, USA
  • Zakaria Maamar, Zayed University, Dubai, United Arab Emirates
  • Greg Madey, University of Notre Dame, USA
  • Deependra Moitra, Infosys Technologies Limited, India
  • Karen Neville, University College Cork , Ireland
  • Wee Keong Ng, Nanyang Technological University, Singapore
  • Paolo Petta, Austrian Research Institute for AI, Austria
  • Ram Ramesh, SUNY at Buffalo, USA
  • Riyaz Sikora, University of Texas at Arlington, USA
  • Rahul Singh, The University of North Carolina at Greensboro, USA
  • David Taniar, Monash University, Australia
  • William Wagner, Villanova University, USA
  • Steven Walczak, University of Colorado at Denver, USA
  • Huaiqing Wang, City University of Hong Kong, Hong Kong
  • Kok Wai Wong, Murdoch University, Western Australia
  • Carson Woo, University of British Columbia, Canada
  • Victoria Yoon, University of Maryland, Baltimore County, USA
  • Daniel Zeng, University of Arizona, USA