Levels of emergence in individual based models: Coping with scarcity of data and pattern redundancy
Authored by Lael Parrott, Guillaume Latombe, Daniel Fortin
Date Published: 2011
DOI: 10.1016/j.ecolmodel.2011.02.020
Sponsors:
National Science and Engineering Research Council of Canada (NSERC)
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Abstract
Pattern Oriented Modelling (POM) is a well-known framework for
designing, parameterizing, and analyzing individual based models (IBM).
It assesses individual or agent based complex systems by applying
inverse modelling on patterns observed in the real system of interest.
However, scarcity of field data is an underlying problem in many
environmental modelling projects and the relationship between the amount
of available data and the domain of applicability of IBMs has hardly
been considered. We argue that choosing the appropriate decision
process, and the traits that represent it, when modelling individuals is
fundamental for the model to be able to generalize when few data are
available, and therefore not representative of the intended domain of
applicability. A pattern being the expression of a given comportment, we
define the notion of level of emergence, and propose to order
comportments according to these levels. This approach may aid in
selecting the appropriate trait for generalization when designing an
IBM. We also show how levels of emergence can be used to assess the
redundancy in patterns. A pattern is redundant with respect to other
patterns when it does not bring new information about the process which
generates it. Since POM makes use of patterns to calibrate the model, one should ensure that the considered patterns are independent, because
redundancy might lead to non-optimal results. Our recommendations thus
provide a way of avoiding some of the potential pitfalls of the POM
framework and contribute to the on-going development of a standard
approach for individual-based modelling. (C) 2011 Elsevier B.V. All
rights reserved.
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movements
systems