Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications (Advances in Intelligent Information Technologies)

451 Pages·2008·9.51 MB·English

by  Vijayan Sugumaran

Distributed Artificial
Intelligence, Agent
Technology, and
Collaborative Applications
Vijayan Sugumaran
Oakland University, USA
InformatIon scIence reference
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Library of Congress Cataloging-in-Publication Data
Distributed artificial intelligence : agent technology and collaborative applications / Vijayan Sugumaran, editor.
p. cm. -- (Information science reference)
Includes bibliographical references and index.
Summary: "This book is a catalyst for emerging research in intelligent information, specifically artificial intelligent technologies and
applications to assist in improving productivity in many roles such as assistants to human operators and autonomous decision-making
components of complex systems"--Provided by publisher.
ISBN 978-1-60566-144-5 (hardcover) -- ISBN 978-1-60566-145-2 (ebook)
1. Distributed artificial intelligence. 2. Artificial intelligence--Industrial applications. I. Sugumaran, Vijayan, 1960-
Q337.D577 2009
006.3--dc22
2008023190
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book set is original material. The views expressed in this book are those of the authors, but not necessarily of
the publisher.
Distributed Arti.cial Intelligence, Agent Technology, and Collaborative Applications is part of the IGI Global series named Advances in
Intelligent Information Technologies (AIIT) Series, ISBN: 1935-3375
If a library purchased a print copy of this publication, please go to http://www.igi-global.com/agreement for information on activating the
library's complimentary electronic access to this publication.
Advances in Intelligent Information Technologies Series (AIIT)
ISBN: 1935-3375
Editor-in-Chief: Vijay Sugumaran, Oakland University, USA
Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications
Information Science Reference • copyright 2008 • 314pp • H/C (ISBN: 978-1-60566-144-5) • US $195.00(our price)
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.
Application of Agents and Intelligent Information Technologies
IGI Publishing • copyright 2007 • 377 pp • H/C (ISBN: 1-59904-265-7) • US $89.96 (our price) • E-Book
(ISBN: 1-59904-267-3) • US $68.76 (our price)
Intelligent agent technology is emerging as one of the most important and rapidly advancing areas. Researchers
are developing a number of agent-based applications and multi-agent systems in a variety of fields, such as: elec-
tronic commerce, supply chain management, resource allocation, intelligent manufacturing, mass customization,
industrial control, information retrieval and filtering, collaborative work, mobile commerce, decision support, and
computer games. Application of Agents and Intelligent Information Technologies presents an outstanding collection
of the latest research associated with intelligent agents and information technologies. Application of Agents and
Intelligent Information Technologies provides a comprehensive analysis of issues related to agent design, implemen-
tation, integration, deployment, evaluation, and business value. This book presents research results and application
of agents and other intelligent information technologies in various domains. Application of Agents and Intelligent
Information Technologies offers the intelligent information technologies that will potentially revolutionize the work
environment as well as social computing.
Intelligent Information Technologies and Applications
IGI Publishing • copyright 2007 • 300+ pp •H/C (ISBN: 978-1-59904-958-8) • US $99.95 (our price)
With the inundation of emergent online- and Web-centered technologies, there has been an increased focus on
intelligent information technologies that are designed to enable users to accomplish complex tasks with relative
ease. Intelligent Information Technologies and Applications provides cutting-edge research on the modeling; imple-
mentation; and financial, environmental, and organizational implications of this dynamic topic to researchers and
practitioners in fields such as information systems, intelligent agents, artificial intelligence, and Web engineering.
The Advances in Intelligent Information Technologies (AIIT) Book Series endeavors to bring together researchers in related fields such as information
systems, distributed Artificial Intelligence, intelligent agents, and collaborative work, to explore and discuss various aspects of design and development
of intelligent technologies. Intelligent information technologies are being used by a large number of organizations for improving productivity in many
roles such as assistants to human operators and autonomous decision-making components of complex systems. While a number of intelligent applica-
tions have been developed in various domains, there are still a number of research issues that have to be explored in terms of their design, implementa-
tion, integration, and deployment over the Internet or a corporate Intranet. The Advances in Intelligent Information Technologies (AIIT) Book Series
aims to create a catalyst for emerging research in this field of growing importance through developing and delivering comprehensive publications for the
betterment of intelligent information technologies and their applications. Through the availability of high-quality resources, the series hopes to further
the development of this field and build upon the foundation of future implications.
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Associate Editors
Forouzan Golshani, Wright State University, USA
Alan R. Hevner, University of South Florida, USA
Kenneth Kendall, Rutgers University - Camden, USA
Stefan Kirn, Universität Hohenheim, Germany
Salvatore T. March, Vanderbilt University, USA
Sudha Ram, University of Arizona, USA
Veda Storey, Georgia State University, USA
Vijay K. Vaishnavi, Georgia State University, USA
Editorial Review 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 Heinz, 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, UAE
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
Table of Contents
Preface ...............................................................................................................................................xvii
Section I
Distributed Agent Applications and Decision Support
Chapter I
Designing Multi-Agent Systems from Logic Specifications: A Case Study ..........................................1
Hong Lin, University of Houston—Downtown, USA
Chapter II
Multi-Agent Architecture for Knowledge-Driven Decision Support ..................................................28
Rahul Singh, University of North Carolina at Greensboro, USA
Chapter III
A Decision Support System for Trust Formalization ...........................................................................47
Farid Meziane, University of Salford, UK
Samia Nefti, University of Salford, UK
Chapter IV
Using Misunderstanding and Discussion in Dialog as a Knowledge Acquisition or Enhancement
Process .................................................................................................................................................65
Mehdi Yousfi-Monod, University of Montpellier, France
Violaine Prince, University of Montpellier, France
Chapter V
Improving E-Trade Auction Volume by Consortium ...........................................................................91
Sungchul Hong, Towson University, USA
Barin N. Nag, Towson University, USA
Dong-qing Yao, Towson University, USA
Chapter VI
Extending Loosely Coupled Federated Information Systems Using Agent Technology ....................116
Manoj.A..Thomas,.Virginia.Commonwealth.University,.USA
. Victoria.Y..Yoon,.University.of.Maryland,.Baltimore.County,.USA
. Richard.Redmond,.Virginia.Commonwealth.University,.USA
Chapter VII
Modeling Fault Tolerant and Secure Mobile Agent Execution in Distributed Systems .....................132
H..Hamidi,.Iran.University.of.Science.&.Technology,.Iran-Tehran
. K..Mohammadi,.Iran.University.of.Science.&.Technology,.Iran-Tehran
Section II
Search and Retrieval
Chapter VIII
Search Engine Performance Comparisons ..........................................................................................148
Xiannong.Meng,.Bucknell.University,.USA
. Song.Xing,.California.State.University—Los.Angeles,.USA
Chapter IX
A User-Centered Approach for Information Retrieval ........................................................................165
Antonio.Picariello,.Università.di.Napoli.Federico.II,.Italy
. Antonio.M..Rinaldi,.Università.di.Napoli.Federico.II,.Italy
Chapter X
Classi.cation and Retrieval of Images from Databases Using Rough Set Theory..............................179
Aboul.Ella.Hassanien,.Cairo.University,.Egypt
. Jafar.M..Ali,.Kuwait.University,.Kuwait
Chapter XI
Supporting Text Retrieval by Typographical Term Weighting............................................................199
Lars.Werner,.University.of.Paderborn,.Germany
. Stefan.Böttcher,.University.of.Paderborn,.Germany
Chapter XII
Web Mining by Automatically Organizing Web Pages into Categories..............................................214
Ben.Choi,.Louisiana.Tech.University,.USA.
. Zhongmei.Yao,.Louisiana.Tech.University,.USA
Chapter XIII
Mining Matrix Pattern from Mobile Users .........................................................................................232
John Goh, Monash University, Australia
David Taniar, Monash University, Australia
Section III
Information Systems and Modeling
Chapter XIV
Conceptual Modeling of Events for Active Information Systems ......................................................261
Salvatore T. March, Vanderbilt University, USA
Gove N. Allen, Brigham Young University, USA
Chapter XV
Information Modeling and the Problem of Universals .......................................................................273
John M. Artz, George Washington University, USA
Chapter XVI
Empirical Inference of Numerical Information into Causal Strategy Models by
Means of Artificial Intelligence ......................................................................................................... 290
Christian Hillbrand, University of Liechtenstein, Principality of Liechtenstein
Chapter XVII
Improving Mobile Web Navigation Using N-Grams Prediction Models ...........................................314
Yongjian Fu, Cleveland State University, USA
Hironmoy Paul, Cleveland State University, USA
Namita Shetty, Cleveland State University, USA
Section IV
Supply Chain Management
Chapter XVIII
Forecasting Supply Chain Demand Using Machine Learning Algorithms ........................................328
Réal Carbonneau, Department of Management Sciences, HEC Montréal, Canada
Rustam Vahidov, John Molson School of Business, Concordia University, Canada
Kevin Laframboise, John Molson School of Business, Concordia University, Canada
Chapter XIX
Supporting Demand Supply Network Optimization with Petri Nets ..................................................366
Teemu Tynjala, Nokia Group, Finland
Compilation of References ..............................................................................................................384
About the Contributors ...................................................................................................................416
Index ................................................................................................................................................423
Detailed Table of Contents
Preface ...............................................................................................................................................xvii
Section I
Distributed Agent Applications and Decision Support
Chapter I
Designing Multi-Agent Systems from Logic Specifications: A Case Study ..........................................1
Hong Lin, University of Houston—Downtown, USA
In Chapter I a program construction method based on γ-Calculus is proposed. The problem to be solved
is specified by first-order predicate logic and a semantic verification program is constructed directly from
the specification. We exploit this method in synthesizing the architectural specifications of multi-agent
systems (MAS) in γ-Calculus based on the logic specifications of the MAS. By enabling the transforma-
tion from the logic specifications to operational specifications of MAS, this method allows the design
of the MAS to be focused on the architectural definition level. It benefits the development of MAS by
enabling logic deduction on behaviors of the MAS, and a design methodology in an incremental fashion.
We present this method by a case study of designing a course information management system.
Chapter II
Multi-Agent Architecture for Knowledge-Driven Decision Support ..................................................28
Rahul Singh, University of North Carolina at Greensboro, USA
In Chapter II we present an Architecture for knowledge-based decision support, delivered through a
Multi-Agent Architecture. We illustrate how to represent and exchange domain-specific knowledge in
XML-format through intelligent agents to create exchange and use knowledge to provide intelligent
decision support. We show the integration of knowledge discovery techniques to create knowledge from
organizational data; and knowledge repositories (KR) to store, manage and use data by intelligent soft-
ware agents for effective knowledge-driven decision support. Implementation details of the architecture,
its business implications and directions for further research are discussed.