Fourth
International ICSC Symposium on
ENGINEERING OF INTELLIGENT
SYSTEMS (EIS 2004)
keynote/plenary
presentations
Multi-Agent
Systems as an Integration Environment for Classical and AI Components
Lenka Lhotska, Olga Stepankova
CZECH TECHNICAL UNIVERSITY IN PRAGUE (CTU),
The GERSTNER LABORATORY (GL) for Intelligent Decision Making and Control
(http://cyber.felk.cvut.cz/gerstner/)
The
multi-agent technology has been recently considered to be much more
suitable for creating open, flexible environment able to integrate
software pieces of diverse nature written in different languages and
running on different types of computers. It enables to design, develop
and implement a comparatively open multi-agent environment suitable
for efficient creating of complex knowledge-based or decision support
systems. Such an environment is able to integrate geographically distributed
knowledge sources or problem solving units. The task under consideration
is located just on the borderline between Software Engineering and
Artificial Intelligence. The idea of software integration based on
efficient communication among parallel computational processes as
well as that of the open architecture (enabling to add new elements
without any change in the others) has been provided by the Software
Engineering area. On the other hand, the multi-agent approach stemming
from the theory of agency, from behavioural models of agents and methods
of agentification of stand-alone programs can be considered as a contribution
of Artificial Intelligence. Multi-agent systems have useful properties,
such as parallelism, robustness, and scalability. Therefore they are
applicable in many domains which cannot be handled by centralized
systems, in particular, they are well suited for domains which require,
for example, resolution of interest and goal conflicts, integration
of multiple knowledge sources and other resources, time-bounded processing
of very large data sets, or on-line interpretation of data arising
in different geographical locations.
Multi
purpose server platforms based on agent and P2P technology
Speaker: Prof. Dr. Claus Rautenstrauch
email: rauten@iti.cs.uni-magdeburg.de
Otto-von-Guericke-Universität Magdeburg
Institut für Technische und Betriebliche Informationssysteme
Postfach 4120 39016 Magdeburg Germany
http://www-wi.cs.uni-magdeburg.de/mitarbeiter/crauten.html
details of abstract forthcoming
The
Road to Mass Customization - Bridging the Gap from Concept to Reality
Speaker:
Prof. Dr. Klaus Turowski,
Chair of Business Informatics and Systems Engineering,
University of Augsburg, Germany
The
advancement of information technology, especially Web-based technologies,
has moved the concept of mass customization in the focus of both the
scientific and the business community. First introduced by Davis primarily
as a strategic marketing concept in 1987, mass customization has been
more broadly defined by Pine II in 1993 as a means to deliver goods
and services, which on the one hand largely meet individual customers'
needs but on the other hand are being produced with near mass production
efficiency without a considerable price premium for those goods and
services. While early adopters of mass customization strategies such
as Dell have already demonstrated the profound impact on both company
performance and industry structure, there is still some uncertainty
about the key factors to successfully put the concept to work in various
settings. In this talk, an overview of the basic engineering, production
management and technological requirements is given, which have to be
combined and coordinated to make mass customization work. Additionally,
the current state of research and future research directions will be
highlighted.
'Dynamic
Vision' - Review and Outlook
Speaker:
Ernst D. Dickmanns
Universitaet der Bundeswehr
Munich (UBM) Germany
Abstract: A brief review on the first two generations of dynamic vision
systems at UBM will be given as an introduction. Applications to ground
and air vehicles as well as space flight will be summarized in video
sequences. The third-generation system 'EMS vision' (Expectation-based,
Multi-focal, Saccadic vision, 1997 - 2003) will be discussed in more
detail. Mission performance on a network of minor roads and cross-country
on grass surface including avoidance of negative obstacles will be demonstrated
by video. After the three-stage basic vision system architecture has
become rather stable by now, an outlook on future developments in visual
machine perception will be given. This encompasses a view how steadily
increasing computing power, communication bandwidth and storage availability
in connection with growing knowledge representation capabilities can
be used for further improvements of system reliability and adaptability
in widening regions of applications.
THE
ART OF BUILDING DECISION TREES IN THE MEDICAL DOMAIN
Speaker:
Peter Kokol
University
of Maribor, Slovenia
Faculty of Electrical Engineering and Computer Science
Many
real-world medical problems are nowadays being handled with tools for
automatic intelligent data analysis. Various methods have been developed
to improve the quality of analysis for specific domains. Application
of any method in a specific domain has special requirements. While medical
experts are not "very good with numbers" we as informaticians must focus
on methods, that are capable of extracting knowledge in a form closer
to human perception (white box methods), e.g. methods that induce decision
trees, classification rules, etc. For the same reason instance methods
based on artificial neural networks (black box methods) that are nevertheless
capable of generalization of nonlinearly separable problems, but have
poor explanatory power are not suitable to be used in the medical domain.
Knowing the "no free lunch theorem" and the fact that normally medical
experts do not have enough time and knowledge to find the best possible
method for their specific problem we developed a Multimethod machine
learning paradigm that can be used to automatically analyze various
machine learning approaches, compare and combine them in a hybrid decision
tree. In the talk we will present the new paradigm and the results obtained
with using it. We will compare various decision tree approaches, purity
measures, ensemble methods and finally hybrid decision trees.
LESSONS
LEARNED FROM DEVELOPMENT OF DECISION-SUPPORT SYSTEMS
Speaker:
Lenka Lhotska
Gerstner Laboratory, Department of Cybernetics,
Czech Technical University in Prague,
Faculty of Electrical Engineering,
Technická 2, CZ-166 27 Prague 6, Czech Republic
ABSTRACT
The aim of the paper is to point to the most important aspects that
must be considered before and during development of a decision-support
system, especially in such a dynamically developing area as medicine.
We have to consider that medical doctors concentrate more on patient's
diagnosis and treatment than on consulting a computer. So introducing
any computer-based system to their work must not be done using force
so that the doctors do not have the feeling they are manipulated and
working on command. Problems, such as motivation of researchers and
users, steps in design and development, human-computer interaction,
problem domain data and knowledge, reasons of failures, are briefly
discussed.
Conference Organizers
University of Madeira,
Portugal
University of Maribor,
Fac. EE and CS, Slovenia
ICSC Canada
