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Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

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  • Guillaume Chérel
  • Clémentine Cottineau
  • Romain Reuillon

Abstract

Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic.

Suggested Citation

  • Guillaume Chérel & Clémentine Cottineau & Romain Reuillon, 2015. "Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-28, September.
    • Handle: RePEc:plo:pone00:0138212
    DOI: 10.1371/journal.pone.0138212
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    References listed on IDEAS

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    1. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
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    2. Aymeric Vi'e & Alfredo J. Morales, 2019. "How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems," Papers 1912.09814, arXiv.org.
    3. Jahel, Camille & Bourgeois, Robin & Bourgoin, Jérémy & Daré, William's & De Lattre-Gasquet, Marie & Delay, Etienne & Dumas, Patrice & Le Page, Christophe & Piraux, Marc & Prudhomme, Rémi, 2023. "The future of social-ecological systems at the crossroads of quantitative and qualitative methods," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    4. Mert Edali & Gönenç Yücel, 2020. "Analysis of an individual‐based influenza epidemic model using random forest metamodels and adaptive sequential sampling," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(6), pages 936-958, November.
    5. Juste Raimbault & Julien Perret, 2019. "Generating urban morphologies at large scales," Post-Print halshs-02265415, HAL.
    6. Juste Raimbault, 2018. "Calibration of a density-based model of urban morphogenesis," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.
    7. Verstegen, Judith A. & Goch, Katarzyna, 2022. "Pattern-oriented calibration and validation of urban growth models: Case studies of Dublin, Milan and Warsaw," Land Use Policy, Elsevier, vol. 112(C).

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