Abstract
Grammar-based Immune Programming (GIP) is a method for evolving programs in an arbitrary language using an immunological inspiration. GIP is applied here to solve the relevant modeling problem of finding a system of differential equations –in analytical form– which better explains a given set of data obtained from a certain phenomenon. Computational experiments are performed to evaluate the approach, showing that GIP is an efficient technique for symbolic modeling.
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Bernardino, H.S., Barbosa, H.J.C. (2011). Inferring Systems of Ordinary Differential Equations via Grammar-Based Immune Programming. In: Liò, P., Nicosia, G., Stibor, T. (eds) Artificial Immune Systems. ICARIS 2011. Lecture Notes in Computer Science, vol 6825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22371-6_19
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DOI: https://doi.org/10.1007/978-3-642-22371-6_19
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