Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Surrogate Assisted Methods for the Parameterisation of Agent-Based
  Models   Parameter calibration is a major challenge in agent-based modelling and
simulation (ABMS). As the complexity of agent-based models (ABMs) increase, the
number of parameters required to be calibrated grows. This leads to the ABMS
equivalent of the \say{curse of dimensionality}. We propose an ABMS framework
which facilitates the effective integration of different sampling methods and
surrogate models (SMs) in order to evaluate how these strategies affect
parameter calibration and exploration. We show that surrogate assisted methods
perform better than the standard sampling methods. In addition, we show that
the XGBoost and Decision Tree SMs are most optimal overall with regards to our
analysis.

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The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
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The categories of this paper are: hep-ex
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: patt-sol
2
The categories of this paper are: math
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
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The categories of this paper are: supr-con