2020
DOI: 10.18564/jasss.4274
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Abstract: The recent advancement of agent-based modeling is characterized by higher demands on the parameterization, evaluation and documentation of these computationally expensive models. Accordingly, there is also a growing request for "easy to go" applications just mimicking the input-output behavior of such models. Metamodels are being increasingly used for these tasks. In this paper, we provide an overview of common metamodel types and the purposes of their usage in an agent-based modeling context. To guide modeler… Show more

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Cited by 13 publications
(9 citation statements)
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“…In interior Alaska, rapidly improving understanding and quantitative predictions of forest distributions is necessary for ecological management under changing climate. Ecologists can increase the pace of model improvements by continuing to build on a growing suite of existing model calibration tools (Fer et al, 2018 ; Oberpriller et al, 2021 ; Pietzsch et al, 2020 ; Speich et al, 2021 ; Tao et al, 2020 ) and team members by trying new methods in different contexts. We provided the first example of a forest model calibration using tree‐ring data allowing us to demonstrate three pragmatic approaches to proceed with model calibration: connecting model outputs to data‐generating processes, determining data‐driven starting conditions from a suite of model simulations, and reducing a high‐dimensional model calibration problem a priori to model fitting for computational efficiency.…”
Section: Discussionmentioning
confidence: 99%
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“…In interior Alaska, rapidly improving understanding and quantitative predictions of forest distributions is necessary for ecological management under changing climate. Ecologists can increase the pace of model improvements by continuing to build on a growing suite of existing model calibration tools (Fer et al, 2018 ; Oberpriller et al, 2021 ; Pietzsch et al, 2020 ; Speich et al, 2021 ; Tao et al, 2020 ) and team members by trying new methods in different contexts. We provided the first example of a forest model calibration using tree‐ring data allowing us to demonstrate three pragmatic approaches to proceed with model calibration: connecting model outputs to data‐generating processes, determining data‐driven starting conditions from a suite of model simulations, and reducing a high‐dimensional model calibration problem a priori to model fitting for computational efficiency.…”
Section: Discussionmentioning
confidence: 99%
“…Combining these techniques to understand mechanisms and improve predictions is a promising path forward (Reichstein et al, 2019 ; Wikle & Hooten, 2010 ). Examples of such ecological applications (Fer et al, 2018 ; Oberpriller et al, 2021 ; Pietzsch et al, 2020 ; Speich et al, 2021 ; Tao et al, 2020 ) are critical for moving beyond implementation barriers and solving urgent ecological problems by bringing these promising tools to larger application‐based audiences.…”
Section: Introductionmentioning
confidence: 99%
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“…In cases of high runtime, replacing the most computationally expensive constituent models with metamodels may be a viable option. Metamodels approximate the input-output behavior of the original model ( Castelletti et al, 2012 ; Christelis and Hughes, 2018 ; Pietzsch et al, 2020 ) and therefore provide simplified representation(s) of more complex models ( Asher et al, 2015 ; Razavi et al, 2012 ). Metamodels leverage the emergent simplicity of complex systems and although there are a variety of methods available to accomplish this, generally metamodels require the complex models (i.e.…”
Section: Scale Issues To Considermentioning
confidence: 99%
“…Meta‐models are doubly simplified, because they are models of models (Urban, 2005; reviewed in Pietzsch et al., 2020). To obtain a meta‐model, first a small‐scale simulation model is run under all sets of conditions that are relevant for large‐scale model analysis.…”
Section: Scaling Approaches Along the Model Chainmentioning
confidence: 99%