0507223 20240103222349.920190803235959.9 000418391500002 10 s. P cav_un_epca*0480157978-80-7464-932-515-24OstravaUniversity of Ostrava2017NovákV.InuiguchiM.ŠtěpničkaM. Compositional model Operator of composition, Causality Conditioning Intervention cav_un_auth*0095925 50 Bína V. CZ cav_un_auth*0101118 Department of Decision Making Theory 50 Jiroušek Radim UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR K Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2019/MTR/jirousek-0507223.pdf cav_un_auth*0353269 GA15-00215S GA ČR CZ The paper presents an algebraic approach to the modeling of causality in systems of stochastic variables. The methodology is based on an operator of a composition that provides the possibility of composing a multidimensional distribution from low-dimensional building blocks taking advantage of the dependence structure of the problem variables. The authors formally define and demonstrate on a hypothetical example a surprisingly elegant unifying approach to conditioning by a single variable and the evaluation of the effect of an intervention. Both operations are realized by the composition with a degenerated distribution and differ only in the sequence in which the operator of the composition is performed. cav_un_auth*0355859 Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /20./ 20170917 20170920 Pardubice CZ IN 10000 10200 10201 2020 2 PR RVO:67985556 http://hdl.handle.net/11104/0298570 S n.a. Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied n.a. Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied n.a. Proceedings Paper Computer Science Artificial Intelligence|Mathematics Applied 2017 SCOPUS PUBMED 000418391500002 WOS cav_un_epca*0480157 Proceedings of the 20th Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty University of Ostrava 2017 Ostrava 15 24 978-80-7464-932-5 340 Novák V. 340 Inuiguchi M. 340 Štěpnička M.