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Plenary Talk 1
On the Fusion of Soft Information
Ronald Yager
Iona College, USA
Abstract: We
discuss the nature and representation of soft information using
granular and other hybrid technologies. We discuss technologies
for fusing and aggregating this type of knowledge. We consider
the problem of fusing soft information with hard information.
Methodologies for formalizing the instructions on how to fuse
information are described. We look at learning as a type of fusion.
Biography: Ronald
R. Yager has worked in the area of machine intelligence for over
twenty-five years. He has published over 500 papers and fifteen books.
He was the recipient of the IEEE Computational Intelligence Society
Pioneer award in Fuzzy Systems. Dr. Yager is a fellow of the IEEE, the
New York Academy of Sciences and the Fuzzy Systems Association. He was
given a lifetime achievement award by the Polish Academy of Sciences
for his contributions. He served at the National Science Foundation as
program director in the Information Sciences program. He was a
NASA/Stanford visiting fellow and a research associate at the
University of California, Berkeley. He has been a lecturer at NATO
Advanced Study Institutes. He has been a distinguished honorary
professor at the Aalborg University Esbjerg Denmark. He is an
affiliated distinguished researcher at the European Centre for Soft
Computing. He received his undergraduate degree from the City College
of New York and his Ph. D. from the Polytechnic University of New York.
Currently, he is Director of the Machine Intelligence Institute and
Professor of Information Systems at Iona College. He is editor and
chief of the International Journal of Intelligent Systems. He serves on
the editorial board of numerous technology journals including the IEEE
Transactions on Fuzzy Systems, Neural Networks, Data Mining and
Knowledge Discovery, IEEE Intelligent Systems, Fuzzy Sets and Systems,
the Journal of Approximate Reasoning and the Journal of Group Decision
Making and Negotiations. He has made fundamental contributions in
decision making under uncertainty and the fusion of information. Much
of his work has been transitioned into commercial applications.
Plenary Talk 2
Designing Social Simulation Using Actual Data
Tadahiko Murata
Faculty of Informatics, Kansai University, Japan
Research Institute for Socionetwork Strategies, Kansai University, Japan
Computation Institute, University of Chicago, USA
Abstract: Aims
of social simulation include to predict a future, to find reasons of
current situations, or to notice problems of a target society. Recently
this research field attracts a lot of researchers from computer
science, artificial intelligence, economics, political science, and son
on. However, most simulations are not based on actual data. That is,
models of target societies are not tuned or identified by the actual
data collected from their target societies. This is because the cost of
collecting actual data from their target societies is expensive.
Therefore, most researches tend to show their simulation results by
varying values of parameters in their model and explain several
scenarios according to the corresponding parameter values. From these
simulation results, we are able to learn several lessons about the
nature of target societies, though, it is difficult to see a
quantitative results or consequences for them. In this talk, we show
several trials to design and develop models of social simulations based
on actually collected data from target societies. We employ multi-agent
simulation models for our social simulations, and show simulation
results for polling place assignment, or assessment for hospital
scrap-and-build. We also show an approach for collecting actual data
within the budget by using a web-based approach.
Biography: Tadahiko
Murata received his Ph. D in 1997 from Osaka Prefecture University,
Japan. After working for Ashikaga Institute of Technology as Assistant
Professor, he joined the Faculty of Informatics, Kansai University as
Associate Professor in 2001. Since 2009, he became Professor of that
faculty. He directs Policy Grid Computing Laboratory, Kansai University
funded by Japanese Government from 2005 to 2010. He was an Associate
Editor of IEEE Transaction on Systems, Man, and Cybernetics, Part B,
and Review of Socionetwork Strategies published from Springer. He was
Chair of Technical Committee of Soft Computing, IEEE SMC Society, and
is currently Chair of Technical Committee of Aware Computing, IEEE SMC
Society, and Japan Chapter Chair of IEEE SMC Society. He received the
Best Presentation Award in 1997 and 2005 from Institute of Systems,
Control and Information Engineers, the Most Active Technical Committee
Award in 2006 from IEEE SMC Society, the Best Presentation Award in
2009 in the International Workshop on Aware Computing. His research
interest includes artificial intelligence, parallel and distributed
computing, and social simulations.
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