0546027 20240111141055.920210930235959.9 10.1007/978-3-030-86772-0_26 Approximations of belief functions using compositional models 13 s. E cav_un_epca*0546852978-3-030-86771-30302-9743Symbolic and Quantitative Approaches to Reasoning with Uncertainty. 16th European Conference, ECSQARU 2021 Proceedings354-366ChamSpringer2021VejnarováJ.WilsonN. Compositional models Entropy of belief functions Decomposable entropy Heuristics Optimality criterion cav_un_auth*0101118 Jiroušek Radim UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory 50 Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0216188 Kratochvíl Václav UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR Department of Decision Making Theory CZ 50 Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2021/MTR/jirousek-0546027.pdf GA19-06569S GA ČR CZ cav_un_auth*0380559 For applications to practical problems, the paper proposes to use the approximations of belief functions, which simplify their dependence structure. Using an analogy with probability distributions, we represent these approximations in the form of compositional models. As no theoretical apparatus similar to probabilistic information theory exists for belief functions, the problems arise not only in connection with the design of algorithms seeking the optimal approximations but even in connection with a criterion comparing two different approximations. With this respect, the application of the analogy with probability theory fails. Therefore, the paper suggests the employment of simple heuristics easily applicable to real-life problems. cav_un_auth*0414314 ECSQARU 2021 : Symbolic and Quantitative Approaches to Reasoning with Uncertainty 20210921 20210924 Praha CZ BB 10000 10100 10102 2022 2 PR RVO:67985556 http://hdl.handle.net/11104/0323626 S 499 0.427 21.58 1.08 84158 Q2 2021 SCOPUS PUBMED WOS pdf cav_un_epca*0546852 Symbolic and Quantitative Approaches to Reasoning with Uncertainty. 16th European Conference, ECSQARU 2021 Proceedings Springer 2021 Cham 354 366 978-3-030-86771-3 Lecture Notes in Computer Science 12897 0302-9743 Vejnarová J. 340 Wilson N. 340