Sepioło, DominikLigęza, Antoni2023-09-212023-09-212023Sepioło D., Ligęza A., A Comparison of Shallow Explainable Artificial Intelligence Methods against Grammatical Evolution Approach. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 89-94, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.12.978-83-66741-92-8http://hdl.handle.net/11652/4787https://doi.org/10.34658/9788366741928.12This paper reports on an ongoing, innovative research in the area of eXplainable Artificial Intelligence (XAI). An XAI task is considered as finding an explanation of the model generated via Machine Learning by identifying the most influential variables for local decision-making. The proposed approach moves the explanatory process to a new, deeper-level dimension. It is oriented towards Model Discovery, i.e. the internal structure and functions of the components. An experiment on Function Discovery via Grammatical Evolution is reported in brief.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionexplainable artificial intelligencegrammatical evolutionstructural regressionmodel-based explainable artificial intelligencewyjaśnialna sztuczna inteligencjaewolucja gramatycznaregresja strukturalnawyjaśnialna sztuczna inteligencja oparta na modelachRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.12