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Recent years saw a significant increase of research emphasis on
modelling of complex systems at various levels of abstraction.
This reflects the natural, human strategy for dealing with
complexity, that of gradual simplification of complex problems and
deriving approximate models. The research challenge is to identify
the appropriate levels of abstraction in any given context and to
evaluate the efficiency and accuracy of the models build on such
abstractions. This broad approach to systems modelling has led to
recent attempts to formalize the balance between accuracy and
generality of systems modelling.
This session will provide a platform for discussion of
leading-edge research contributions to multi-resolution and
granular modelling of systems. The range of application domains
that are relevant to this session includes, but is not limited to:
- system optimisation, scheduling and
resource allocation,
- modelling of biological and molecular
systems,
- modelling agroecosystems; linking
genetic, physical and human dimensions
- modelling in business and social sciences,
- set theoretic research (sets and interval
analysis, fuzzy sets, rough sets, shadowed sets),
- granulation and clustering algorithms,
- communication between systems described at
various levels of granularity,
- empirical verification of models,
Within this context we are soliciting both technical papers
dealing with specific cases of multi-resolution and granular
modelling and the papers addressing strategic vision of the
development of modelling paradigms for complex systems.
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