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"Managing Complexity, Reducing Perplexity" is devoted to an
overview of the status of the art in the study of complex systems,
with particular focus on the analysis of systems pertaining to
living matter. Both senior scientists and young researchers from
diverse and prestigious institutions with a deliberately
interdisciplinary cut were invited, in order to compare approaches
and problems from different disciplines. The common aim of the
contributions was to analyze the complexity of living systems by
means of new mathematical paradigms that are more adherent to
reality and which are able to generate both exploratory and
predictive models that are capable of achieving a deeper insight
into life science phenomena.
”Managing Complexity, Reducing Perplexity” is devoted to an
overview of the status of the art in the study of complex systems,
with particular focus on the analysis of systems pertaining to
living matter. Both senior scientists and young researchers from
diverse and prestigious institutions with a deliberately
interdisciplinary cut were invited, in order to compare approaches
and problems from different disciplines. The common aim of
the contributions was to analyze the complexity of living systems
by means of new mathematical paradigms that are more adherent to
reality and which are able to generate both exploratory and
predictive models that are capable of achieving a deeper insight
into life science phenomena.
This work aims to foster the interdisciplinary dialogue between
mathematicians and socio-economic scientists. Interaction among
scholars and practitioners traditionally coming from different
research areas is necessary more than ever in order to better
understand many real-world problems we face today. On the one hand,
mathematicians need economists and social scientists to better
address the methodologies they design in a more realistic way; on
the other hand, economists and social scientists need to be aware
of sound mathematical modelling tools in order to understand and,
ultimately, solve the complex problems they encounter in their
research. With this goal in mind, this work is designed to take
into account a multidisciplinary approach that will encourage the
transfer of knowledge, ideas, and methodology from one discipline
to the other. In particular, the work has three main themes:
Demystifying and unravelling complex systems; Introducing models of
individual behaviours in the social and economic sciences;
Modelling socio-economic sciences as complex living systems.
Specific tools examined in the work include a recently developed
modelling approach using stochastic game theory within the
framework of statistical mechanics and progressing up to modeling
Darwinian evolution. Special attention is also devoted to social
network theory as a fundamental instrument for the understanding of
socio-economic systems.
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