We propose a novel approach to parameter synthesis for parametrised Kripke structures and CTL specifications. In our method, we suppose the parametrisations form a semi-algebraic set and we utilise a symbolic representation using the so-called cylindrical algebraic decomposition of corresponding multivariate polynomials. Specifically, we propose a new data structure allowing to compute and efficiently manipulate such representations. The new method is significantly faster than our previous method based on SMT. We apply the method to a set of rational dynamical systems representing complex biological mechanisms with non-linear behaviour.
CITATION STYLE
Beneš, N., Brim, L., Geletka, M., Pastva, S., & Šafránek, D. (2019). Accelerating Parameter Synthesis Using Semi-algebraic Constraints. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11918 LNCS, pp. 27–45). Springer. https://doi.org/10.1007/978-3-030-34968-4_2
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