Data-Informed Parameter Synthesis for Population Markov Chains
| Authors | |
|---|---|
| Year of publication | 2019 |
| Type | Article in Proceedings |
| Conference | 17th International Conference on Computational Methods in Systems Biology (CMSB 2019) |
| MU Faculty or unit | |
| Citation | HAJNAL, Matej, Nouvian MORGANE, Tatjana PETROV and David ŠAFRÁNEK. Data-Informed Parameter Synthesis for Population Markov Chains. In Bortolussi, L. and Sanguinetti, G. 17th International Conference on Computational Methods in Systems Biology (CMSB 2019). LNBI 11773. Neuveden: Springer Nature, 2019, p. 383-386. ISBN 978-3-030-31303-6. Available from: https://dx.doi.org/10.1007/978-3-030-31304-3_32. |
| web | https://doi.org/10.1007/978-3-030-31304-3_32 |
| Doi | http://dx.doi.org/10.1007/978-3-030-31304-3_32 |
| Keywords | population models; formal methods; model checking |
| Description | In this work, we investigate how to obtain the parameters for single agent behaviour, based on data collected for a population. Measurements for different population sizes are especially important when studying social feedback: an adaptation of individual’s behaviour to the changing context of the population. |
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