Dan Dolk
Department of Systems Management
Naval Postgraduate School
Monterey, California 93943-5103
Tel: (408) 656-2260
Fax: (408) 656-3407
E-mail: drdolk@nps.navy.mil
Steven O. Kimbrough
University of Pennsylvania
3620 Locust Walk, #1300
Philadelphia, PA 19104-6366
Tel: (215) 898-5133
Fax: (215)898-3664
E-mail: sok@grace.wharton.upenn.edu
kimbrough@wharton.upenn.edu
http://opim.wharton.upenn.edu/~sok/logicmodeling/hicss98call.html
See also: opim.wharton.upenn.edu/~sok/logicmodeling/
Hemant K. Bhargava
Code AS/BH
Naval Postgraduate School
555 Dyer Road, Room 229
Monterey, CA 93943-5103
Tel: (408) 656-2264
Fax: (408) 656-3407
E-mail: bhargava@cs.nps.navy.mil
Stephen F. Roehrig
The H. John Heinz III School of Public Policy and Management
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213-3890
Tel: (412) 268-8783
Fax (412) 268-7036
E-mail: roehrig+@andrew.cmu.edu
Don Nute
DFepartment of Philosophy
107 Peabody Hall
University of Georgia
Athens, Georgia 30602
Tel: (706) 542-2823
Fax: (706) 542-2839
E-mail: dnute@ai.uga.edu
The aim of the Intelligent Systems and Active DSS minitrack is fourfold:
(i) to summa-rise past research work in this area and draw lessons from
it;
(ii) to explore the possibility of developing a new generation of intelligent
systems;
(iii) to suggest an enhanced methodology for using support technology in
problem solving and decision making, and
(iv) to devise implementation approaches for an effective use of the new
support technology in organizations.
The next generation of support technology will probably include (but
is not limited to):
* fuzzy logic,
* approximate reasoning,
* intelligent agents and filters
* uncertainty modeling,
* multiple criteria decision analysis,
* object-oriented development environments
* neural networks,
* genetic algorithms for interactive planning, problem solving and decision
making, group support and decision
Research methods will include: (i) developing a methodology for planning,
problem solving and decision making with the help of a hyperknowledge support
technology; (ii) using support systems constructs as research instruments
to better understand group processes, problem solving, decision making,
the forming of strategic plans and the effectiveness of management; (iii)
building and validating theories on effective decision support, which eventually
should (with the hybrid system) prove to, (iv) form a new generation of
intelligent systems software.
There is an overall ideology for developing support based on intelligent
systems which has been gradually emerging in practice:
* develop the support technology interactively with the users,
* use the Windows or a compatible environment, which allows the use of
* affordable computer hardware and software,
* object oriented programming to produce fast and effective computer code,
and
* intuitively understandable, self-guiding visible logical constructs in
the support system
Christer Carlsson
Inst. for Advanced Mgmt Sys.Research
Abo Akademi University
DataCity A 3210
20520 Abo
FINLAND
E-mail: Christer.Carlsson@abo.fi
Pirkko Walden
Inst. for Advanced Mgmt Sys.Research
Abo Akademi University
DataCity A 3210
20520 Abo
FINLAND
E-mail: pwalden@abo.fi
Tawfik Jelassi
Euro-Arab Management School
C/.C=E1rcel Baha 3
18001 Granada
SPAIN
E-mail: Jelassi@eams.fundea.es
(At Insead: jelassi@insead.fr)
The minitrack focuses on complex and chaotic systems. The minitrack encompasses both (a) theoretical and applied models describing these systems, and (b) techniques such as artificial neural nets, genetic algorithms, fractals, etc., used in modeling. Theoretical developments, empirical applications, and experimental designs of physical or economic systems would be included.
The topics that the minitrack will address are:
- modeling of complex and chaotic (C&C) systems
- characterization of the behavior of C&C systems
- prediction of complex and chaotic systems
- optimization of C&C models
- optimization of model form
- modelling C&C with artificial neural networks
- optimization of C&C with genetic algorithms
- global optimization approaches
- decomposition of complex processes
- mutual information models and approaches
- self organization models in complex processes
- combinations of the above
Sul Kassicieh
Anderson School of Management
University of New Mexico
Albuquerque, NM 87131
Tel: (505) 277-8881
Fax: (505) 277-7108
E-mail: kasicieh@unm.edu
http//:asm.unm.edu
Tom Paez
Sandia National Laboratories
Organization 9741
P.O. Box 5800
Alburquerque, NM 87185
Tel: (505) 844-7052
Fax: (505) 844-0078
E-mail: tlpaez@sandia.gov
Gautam Vora
Anderson School of Management
University of New Mexico
Albuquerque, NM 87131
Tel: (505) 277-0669
Fax: (505) 277-7108
E-mail: vora@unm.edu
The aim of the Uncertainty Modeling and Approximate Reasoning minitrack is four-fold: (i) to summarize past research work in this area and draw lessons from it; (ii) to explore the possibility of developing a new paradigm for modeling, problem solving and decision making; (iii) to suggest an enhanced methodology for incorporating new modeling theory in support systems, and (iv) to develop more effective implementation methods for an effective use of support technology in organizations.
The next generation of modeling tools and support systems for interactive
planning, problem solving and decision making, by individuals or by groups
of users will include (but is not limited to) the following:
* fuzzy logic,
* approximate reasoning,
* intelligent agents and filters
* uncertainty modeling,
* multiple criteria decision analysis,
* object-oriented development environments
* neural networks,
* genetic algorithms.
Christer Carlsson
Inst. for Advanced Mgmt Sys.Research
Abo Akademi University
DataCity A 3210
20520 Abo
FINLAND
E-mail: Christer.Carlsson@abo.fi
This minitrack concerns the impact of increased competition on the modeling technologies and software systems that are widespread in the telecommunications industry. It will investigate the radical changes in modeling and technology which have characterized the abrupt transition from a regulated to a competitive environment.
Papers are solicited in the following areas:
* modeling the incentives of regulated firms under alternative regulatory
structures
* modeling consumer choices when faced with competitive alternatives
* impact of competitive pressures on software design and implementation
* impacts/uses of distributed processing in advanced telecommunications
networks
* use of GIS and data mining tools for telecommunications information analysis
Don Kridel
Department of Economics
College of Arts and Sciences
8001 Natural Bridge Road
University of Missouri - St. Louis
St. Louis, MO 63121-4499
Tel: 314-516-5351 (Dept.)
Fax: 314-516-5352
E-mail: kridel@jinx.umsl.edu
Dennis Weisman
Kansas State University
Department of Economics
Waters Hall
Manhattan, KS 66506-4001
E-mail: weisman@ksu.edu
David Castillo
Motorola Satellite Communications Division
2501 South Price Road
MS OSC-H
Chandler, AZ 85248
E-mail: David_Castillo@sat.mot.com
The aim of this minitrack is to provide a forum for researchers and practitioners interested in modelling methods and methodologies to meet, present their research and experience, and exchange ideas on the topic. Researchers seek to find yardsticks and objective measures of methods, whereas practitioners are usually more interested in the quot;goodness" of the methods, and the ease of application and learning of the methods. We hope to solicit papers from both sides. The research contributions can be new ways of evaluating methods or empirical research about the use of methods; and the practitioners contributions can range from experiences in selecting a method to evaluation of a particular method. Another possible theme is the suitability of general purpose methods to work together with new software frameworks such as client\server applications and web-enabled applications. Also the evaluation of the much heralded capabilities of methods to support large scale reuse and framework or component based development is another very important topic area.
Relevant topics for this minitrack include
(i) Theoretical foundations for evaluating modelling methods and methodologies
(ii) Evaluation techniques for
(iii) Reports on evaluation results
(iv) Advance application of modeling techniques:
Keng Siau
Department of Management
209 College of Business Administration
University of Nebraska - Lincoln
Lincoln, NE 68588-0491, USA
Email: klsiau@unlinfo.unl.edu
Tel: (402) 472-3078
Fax: (402) 472-5855
E-mail: klsiau@unlinfo.unl.edu
URL: http://www.ait.unl.edu/doc2/faculty/siau/home.htm
Matti Rossi
Department of Computer Information Systems
Georgia State University
Colege of Business Administration
Box 4015
Atlanta, Georgia 30302-4015
E-mail: mor@jyu.fi
URL: http://www.jyu.fi/~mor/
The minitrack covers the theoretical issues related to data mining, learning-by-examples, knowledge acquisition, knowledge discovery, and inductive decision making. A goal for the minitrack is to build a foundation for the application of data mining and knowledge discovery from an interdisciplinary perspective including artificial intelligence, psychology, computer science, statistics, and management.
Some of the relevant topics are new data mining algorithms, analysis of existing algorithms or applications, comparison of inductive learning and data mining concepts, new ways of thinking about statistics, data mining measures, knowledge re-use, acquisition of qualitative knowledge, data visualization technique to further understand the model/data structure, maintenance and adaptation of algorithms, human factors in decision modeling, task characteristics, and economics of decision making. The papers should stress the broader applicability of the techniques rather than only successful deployment on an individual project.
H. Michael Chung *(send papers here)
Department of Information Systems
College of Business Administration
California State University, Long Beach
Long Beach, CA 90840-8506
Tel: (562) 985-7691
Fax: (310) 985-5543
E-mail: hmchung@csulb.edu
Paul Gray
Programs in Information Science
Claremont Graduate School
Claremont, CA 91711-6190
Tel: (909) 621-8209
Fax: (909) 621-8564
E-mail: grayp@cgs.edu
Michael V. Mannino
Dept. Of Mgmt. Science
Box 353200
School of Business
University of Washington
Seattle, WA 98195
Tel: 206-685-4762
Fax: 206-685-9392
E-mail: zmann@u.washington.edu
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