Digital Library

of the European Council for Modelling and Simulation



Collaborative Granular Modeling And Simulation


Witold Pedrycz

Published in:


(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


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



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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