Intelligent Information Agents: Agent-Based Information Discovery and Management on the Internet

513 Pages·1999·19.18 MB·English

by  Matthias Klusch (auth.)

Intelligent Information Agents
Springer
Berlin
Heidelberg
New York
Barcelona
Hong Kong
London
Milan
Paris
Singapore
Tokyo
Matthias Klusch (Ed.)
Intelligent
Information Agents
Agent -Based Information Discovery
and Management on the Internet
With 113 Figures and 22 Tables
Springer
Editor
Matthias Klusch
Computer Science Department
Technical University of Chemnitz
Strasse der Nationen 62
09107 Chemnitz, Germany
E-mail: [email protected]
WWW: http://www.informatik. tu-chemnitz.derklusch
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Die Deutsche Bibliothek - Cip-Einheitsaufnahme
Intelligent information agents: agent based information discovery
and management on the Internet; with tablesl Matthias Klusch
(ed.). - Berlin; Heidelberg; New York; Barcelona; Hong Kong;
London; Milan; Paris; Singapore; Tokyo: Springer, 1999
ISBN 978-3-642-64223-4
ACM Subject Classification (1998): I.2.11, C.2, H.2-5
ISBN 978-3-642-64223-4 Springer-Verlag Berlin Heidelberg New York
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ISBN-13: 978-3-642-64223-4 e-ISBN-13: 978-3-642-60018-0
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Foreword
We live in a world that is becoming increasing distributed and service
oriented, and this is reflected in the computer systems we design, build,
manage and use. We rely on these systems to support our everyday activi
ties through electronic mail, document interchange and other collaboration
technologies.
The Internet and World Wide Web [63] allow us to access multimedia data
and knowledge located throughout the world. Clearly, these new technologies
present enormous opportunities for posting, finding, organizing and sharing
vast amounts of information.
Further, electronic commerce is gaining a foothold on the WWW, and
presents a vital complement to the normal business activities conducted by
corporations and individuals. New paradigms are emerging for e-commerce,
both business-to-business e-commerce and entrepreneurial e-commerce, al
lowing consumers to be linked directly with producers, and thereby bypassing
the traditional "middleperson."
In the real world, our service-oriented approach to doing business leads
us to delegate both responsibility and authority for certain negotiations and
decisions to our representatives or agents, such as real-estate agents, stock
brokers, personal shoppers, secretaries, etc. The major issues confronting con
sumers of on-line information include access and availability of information
resources, confidence in the veracity of the data provided, and an assessment
of the trustworthiness of the provider.
If we extend the metaphor to cyberspace, we would like our collection of
trusted and reliable agents to represent us in cyberspace in order to:
- search for, acquire, analyze, integrate, and archive data from multiple het
erogeneous distributed sources [19, 127, 152, 157, 230, 361, 724],
- inform users when new data of special interest becomes available [602],
- negotiate for, purchase and receive information, goods and services [334,
335],
- explain the relevance, quality and reliability of that information [448, 449],
and
- adapt and evolve to changing conditions [164, 227, 303, 333, 364, 571].
VI Foreword
Thus, agents will have a role in our evolving information infrastructure,
if they caIlL be useful to people, organizations and information systems.
This book addresses the role of intelligent information agents in advanced
information systems. In order for agents to cooperate, they must share com
mon objectives, understand each other, communicate their goals and tasks,
and be able to share data, information and knowledge. They may also be part
of coordinated groups of agents, organized to cooperate in problem solving.
There are two specific areas, among others, that can make use of intelligent
agents.
Intelligent Integration of Information
The DARI>A-sponsored research program on the "Intelligent Integration of
Information" (1*3) focused on the acquisition, integration and dissemina
tion of data, information and knowledge. Principal investigators in the 1*3
program produced a three-layer Reference Architecture consisting of various
types of services, including facilitation and brokerage services, mediation and
integration services, and wrapping and data access services.
This three-layer service architecture is amenable to intelligent agents that
can support the services offered at each layer [334]. Several chapters in this
book address important topics related to 1*3, but much work remains to be
done in this area.
Electroni<: Commerce
Many web sites offer "portals" which serve as "ports of entry" into the Inter
net and World Wide Web. These include such famous sites as Yahoo, Excite,
Altavista, and Netscape, to name a few. They offer users Internet services,
such as free e-mail, paging services, stock quotes and tailored news (including
tailored ads), as well as other web-based services. The goal is to win "brand
loyalty" from their subscribers who then read the numerous advertisements,
and sometimes visit advertiser web sites to purchase products.
E-commerce is growing rapidly on the web. Electronic commerce today
has several components, including: 1) interactive business and financial trans
actions, 2) electronic cataloguing, 2) electronic order-tracking services, 3) au
tomatic billing and payment services, 4) electronic funds transfer, 5) vendor
registration and electronic "brand naming" , 6) automatic ordering, contract
ing and procurement, 7) advertising of products, 8) data mining of consumer
information for customer profiling, and 9) customization of advertisements
to have more effective impact on prospective customers.
One very important area is business-to-business e-commerce where com
panies sell their products directly to their corporate customers. For exam-
Foreword VII
pIe the Boeing Company allows airlines to order parts from an integrated,
authoritative parts catalog. This 24-hour, seven-days-a-week service allows
customers anywhere in the world to access the catalog and make purchases.
CISCO Systems, a vendor of network routers, estimates that customers will
purchase over 5 billion USD via its web site this year.
One phenomenal organization, Amazon.com Books Inc., sells only via the
Web, as opposed to its competitors, such as Barnes and Noble, which have
retail outlets as well as a web outpost. At Amazon.com customers can post
book reviews and authors can post self-conducted interviews. When a reader
makes a selection, titles of related books are presented. Customers purchase
titles which are then ordered from suppliers, thereby reducing inventory.
Here agents can play an important role in profiling user preferences, sug
gesting related titles, alerting them when specifically requested titles have
arrived, and linking them to this shared "knowledge" space. In addition to
a comprehensive catalog of holdings, web sites such as Amazon.com inform
users as to inventory availability, and delivery times, thereby allowing users to
have confidence that the goods will be delivered in a timely fashion. We need
to gain a better understanding of the processes that draw users to web sites,
their behavior and interactions with the products and services offered, and
the way agents can assist both consumers and producers in forming lasting
and productive relationships.
It is this last point, forming lasting and productive relationships, that
seems to be a driver on the web, and this is very much in keeping with
the service-oriented approach to building advanced information systems. We
see companies forming strategic alliances to better serve their customers by
providing ene-to-end services. The most recent example is America Online's
purchase of Netscape Corporation, and its forming a strategic alliance with
Sun Microsystems, which contributes a large world-wide sales force and the
hardware and software to build and manage Web sites.
This book of very topical and relevant contributions will help us to un
derstand the research and practical issues involved in building Intelligent
Information Agents, and how to transition them from the research labs
into the infrastructure of our advanced information systems.
Larry K erschberg
Professor and Director of
Center for Information Systems Integration and Evolution
George Mason University
Fairfax, Virginia, USA
December 1998
VIII Foreword
Preface:
Intelligent Information Agents in Cyberspace
Research and development on intelligent information agents is of rapidly in
creasing importance. In fact, it can be seen as one of the key technologies
for the Internet and the World Wide Web. But what are information agents,
and what impact will they have on computing early in the next century?
Roughly speaking, information agents are computational software systems
that have access to multiple, heterogeneous and geographically distributed
information sources. Such agents may assist their users in finding useful, rel
evant information; in other words, managing and overcoming the difficulties
associated with "information overload". Information agents not only have
to provide transparent access to many different information sources in the
Internet, but also to be able to retrieve, analyze, manipulate, and integrate
heterogeneous data and information on demand, preferably in a just-in-time
fashion.
In part, there are many approaches and implemented solutions available
from advanced databases, knowledge bases, and distributed information sys
tems technology to meet some of these demands. In addition, effective and
efficient access to information on the Web has recently become a critical re
search area. Limitations of search engines and the presence of semi-structured
and unstructured information has led to the development of new query lan
guages and data models. But the development of smart information agents
in an open, dynamically changing cyberspace is a more tough challenge. It
requires strong expertise from several related research areas, such as Artificial
Intelligence (AI), Distributed AI, Information Retrieval, Cognitive Sciences,
Computer Supported Collaborative Work (CSCW), and Human-Computer
Interaction.
Information agents can be classified into the following broad categories:
- Non-cooperative or cooperative information agents, depending on their abil
ity to cooperate with each other for the execution of their tasks. Several
protocols and methods are available for achieving cooperation among au
tonomous information agents in different scenarios (see Part I of the book),
like hierarchical task delegation, simple or complex contracting, and decen
tralized negotiation.
- Rational information agents (see Part II) are utilitarian in an economic
sense. They behave and may even collaborate together to increase their own
)( f>reface
benefits. One main application domain of such rational agents is automated
trading and electronic commerce in the Internet. Examples include the
variety of available ShopBots, and systems for agent-mediated auctions on
the Web.
- Adaptive information agents (see Part III) are able to adapt themselves
to changes in networks and information environments. Examples of such
agents are learning personal assistants on the Web.
- Mobile information agents (see Part IV) are able to travel autonomously
through the Internet. Such agents may enable, e.g., dynamic load bal
ancing in large-scale networks, reduction of data transfer among informa
tion servers and applications, and migration of small business logic within
medium-range corporate intranets on demand.
Figure 0.1 shows this classification as an extension of Franklin and
Gaesser's ta.xonomy of agents in [222].
Autonomous Agents
Biological Agents Computational Agents Robotic Agents
~
Software Agents Artificial Life Agents
Viruses Task-Specific Agents Entertainment Agents
Information Agents
Non-Cooperative Cooperative
....... ~ ~
Adaptive Rational Mobile Adaptive Rational Mobile
Fig. 0.1. A classification of information agents
Examples for each of the categories of non-cooperative information agents
are shown in Fig. 0.2.