Reasoning in Complex and Uncertain Systems:
A Framework for Human-centred Information Processing
The synergy of research insights from complex systems modelling, uncertain information
processing and information abstraction has motivated our research into a unifying framework of
Granular Computing arose as a response to the urgent need for intelligent processing
of empirical data, that are now commonly available in vast quantities, into a humanly
manageable knowledge represented as domain models at different levels of abstraction.
In this sense, granular computing offers a landmark
change from the machine-centric to human-centric processing of information
In other words, we move from heuristics (representing approximate
methods of solving detailed problems) to granular computing ( representing
detailed solutions to approximated problems).
The theoretical foundations of granular computing are very
sound and involve set theory (interval mathematics), fuzzy sets, rough sets and random
sets utilised for the representation of uncertainty and information abstractions.
There has been a tremendous increase in the research interest in
Granular Computing duting the last decade
(Granular Computing: An Introduction, Kluwer, 2002). An important
reason behind this has been a realisation that the real world does not lend
itself to a manageable description/modelling using numerical data only.
The vast quantities of raw data that are now available, need to be processed through
intelligent abstraction, into higher-level entities, i.e. information granules.
Such an approach mirrors what humans do when faced with the task of processing
We argue that the development of human-centric
computer technologies, aiming at overcoming the limitations of the current
machine-centric approaches, represents one of the most important challenges of computer science.
The research agenda of human centricity has certainly gained visibility and prominence in the last
10 years. It is quite remarkable that
the spectrum of application and research areas that
have adopted information granulation as a successful strategy for dealing with
information complexity covers such diverse fields as bioinformatics, image
understanding, environmental monitoring, urban sustainability, to mention few
most visible in the literature.
In our recent book
(Human-centric information processing through granular
modelling, Springer, 2009) we document milestone contributions to
human-centric information processing research and demonstrate the emerging
computational methods and the processing environments that arose from these
However, more research is needed to understand the mechanisms
of human information abstraction. In this sense the interaction
between the research into granular computing and the psychology, biological, physical and medical sciences
needs to be enhanced to the benefit of all collaborating parties.
Also the spectrum of applications of granular computing needs to be broadened
to include not only the science domain applications but also applications
from arts and humanities. It seems that the improvement of understanding of
the higher-level information processing that occurs in social interactions
and in arts could offer a valuable guidance regarding
the computer-based information granulation.
In short, granular computing promises to be a fruitful area for
interdisciplinary research and we believe that it will underpin much
of the scientific progress in the 21-st century.
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