Established in 2005 under support of MŠMT ČR (project 1M0572)

Publications

Fully Probabilistic Design: Basis and Relationship to Bayesian Paradigm

Typ:
Conference paper
Authors:
Proceedings name:
3rd International Workshop on Data - Algorithms - Decision Making
Publisher:
ÚTIA
Serie:
Praha
Year:
2007
Keywords:
multiple participant, decision making, fully probabilistic d
Anotation:
There is a wide range of axiomatic formulations of decision making (DM) under uncertainty and incomplete knowledge, e.g. [7]. It seems, however, that none of them fits satisfactorily to closed decision loops in which the selected actions influence distributions describing them, cf. [1], part three. This contribution is an engineering attempt to fill the gap. The adjective “engineering” means that the overall picture is preferred over subtleties like measurability of various mappings. The contribution serves primarily as a formalized justification of the fully probabilistic design (FPD) of decision-making strategies, [4, 2, 5]. The FPD generates optimal non-anticipative strategy as minimizer of the Kullback-Leibler divergence [6] of the probability density function (pdf), describing behavior of the closed decision loop, on an ideal pdf, describing desired behavior of the closed decision loop.
 
Copyright 2005 DAR XHTML CSS