期刊
出版社
WILEY
DOI: 10.1002/cnm.3470
关键词
agent‐ based modelling; in silico trials; tuberculosis; verification
类别
资金
- [SC1-PM-16-2017-777123]
This study introduces a general framework for verification of Agent-Based models to evaluate numerical errors, focusing on the quantification of approximation errors for UISS-TB. The step-by-step procedure allows for systematic identification and quantification of numerical errors.
Agent-based models (ABMs) are a powerful class of computational models widely used to simulate complex phenomena in many different application areas. However, one of the most critical aspects, poorly investigated in the literature, regards an important step of the model credibility assessment: solution verification. This study overcomes this limitation by proposing a general verification framework for ABMs that aims at evaluating the numerical errors associated with the model. A step-by-step procedure, which consists of two main verification studies (deterministic and stochastic model verification), is described in detail and applied to a specific mission critical scenario: the quantification of the numerical approximation error for UISS-TB, an ABM of the human immune system developed to predict the progression of pulmonary tuberculosis. Results provide indications on the possibility to use the proposed model verification workflow to systematically identify and quantify numerical approximation errors associated with UISS-TB and, in general, with any other ABMs.
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