A Note on Approximation of Shenoy's Expectation Operator Using Probabilistic Transforms

0523947 - ÚTIA 2021 RIV GB eng J - Článek v odborném periodiku
Jiroušek, Radim - Kratochvíl, Václav - Rauh, J.
A Note on Approximation of Shenoy's Expectation Operator Using Probabilistic Transforms.
International Journal of General Systems. Roč. 49, č. 1 (2020), s. 48-63. ISSN 0308-1079. E-ISSN 1563-5104
Grant ostatní: GA ČR(CZ) GA19-06569S
Institucionální podpora: RVO:67985556
Klíčová slova: Expectation * belief function * probabilistic transform * commonality function * utility * ambiguity * Choquet integral
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 2.080, rok: 2020
Způsob publikování: Omezený přístup
http://library.utia.cas.cz/separaty/2020/MTR/jirousek-0523947.pdf https://www.tandfonline.com/doi/full/10.1080/03081079.2019.1692006

Recently, a new way of computing an expected value in the Dempster-Shafer theory of evidence was introduced by Prakash P. Shenoy. Up to now, when they needed
the expected value of a utility function in D-S theory, the authors usually did it indirectly: first, they found a probability measure corresponding to the considered belief function, and then computed the classical probabilistic expectation using this probability measure. To the best of our knowledge, Shenoy's operator of expectation is the first approach that takes into account all the information included in the respective belief function. Its only drawback is its exponential computational complexity. This is why, in this paper, we compare five different approaches defining probabilistic representatives of belief function from the point of view, which of them yields the best approximations of Shenoy's expected values of utility functions.
Trvalý link: http://hdl.handle.net/11104/0308327