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Digital Library of the
European Council for Modelling and Simulation |
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Title: |
Collaborative
Granular Modeling And Simulation |
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Authors: |
Witold Pedrycz |
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Published in:
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(2010).ECMS
2010 Proceedings edited by A Bargiela S A Ali D
Crowley E J H Kerckhoffs. European Council for
Modeling and Simulation. doi:10.7148/2010 ISBN:
978-0-9564944-0-5 24th
European Conference on Modelling and Simulation, Simulation Meets Global Challenges Kuala
Lumpur, June 1-4 2010 |
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Citation
format: |
Pedrycz, W. (2010). Collaborative
Granular Modeling And Simulation. ECMS 2010 Proceedings edited by A Bargiela S A Ali D Crowley E J H Kerckhoffs
(pp. 5-13). European Council for Modeling and Simulation. doi:10.7148/2010-0005-0014 |
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DOI: |
http://dx.doi.org/10.7148/2010-0005-0014 |
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Abstract: |
With
the remarkably diversified plethora of design methodologies and algorithmic
pursuits present today in system modeling including fuzzy modeling, we also
witness a surprisingly high level of homogeneity in the sense that the
resulting models are predominantly concerned with and built by using a data
set coming from a single data source. In
this study, we introduce a concept of collaborative granular modeling. In a
nutshell, we are faced with a number of separate sources of data and the
resulting individual models formed on their basis. An ultimate objective is
to realize modeling at the global basis by invoking effective mechanisms of
knowledge sharing and collaboration. In this way, each model is formed not
only by relying on a data set that becomes locally available but also is
exposed to some general modeling perspective by effectively communicating
with other models and sharing and reconciling revealed local sources of
knowledge. Several
fundamental modes of collaboration (by varying with respect to the levels of
interaction) are investigated along with the concepts of collaboration
mechanisms leading to the effective way of knowledge sharing and reconciling
or calibrating the individual modeling points of view. The predominant role
of information granules with this regard is stressed. For
illustrative purposes, the underlying architecture of granular models
investigated in this talk is concerned with rule-based topologies and rules
of the form “if Ri then fi” with Ri being |
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