BACK to VOLUME 42 NO.6

Kybernetika 42(6):629-646, 2006.

Decision-Making Under Uncertainty Processed by Lattice-Valued Possibilistic Measures

Ivan Kramosil


Abstract:

The notion and theory of statistical decision functions are re-considered and modified to the case when the uncertainties in question are quantified and processed using lattice-valued possibilistic measures, so emphasizing rather the qualitative than the quantitative properties of the resulting possibilistic decision functions. Possibilistic variants of both the minimax (the worst-case) and the Bayesian optimization principles are introduced and analyzed.


Keywords: decision making under uncertainty; complete lattice; lattice-valued possibilistic measures; possibilistic decision function; minimax and Bayesian optimization;


AMS: 28E10; 28E99;


download full-text.pdf
download abstract.pdf

BIB TeX

@article{kyb:2006:6:629-646,

author = {Kramosil, Ivan},

title = {Decision-Making Under Uncertainty Processed by Lattice-Valued Possibilistic Measures },

journal = {Kybernetika},

volume = {42},

year = {2006},

number = {6},

pages = {629-646}

publisher = {{\'U}TIA, AV {\v C}R, Prague },

}


BACK to VOLUME 42 NO.6