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Abstract

Fully Probabilistic Design: Basis and Relationship to Bayesian Paradigm

Kárný Miroslav

: 3rd International Workshop on Data - Algorithms - Decision Making, p. 8-8 , Eds: Janžura Martin, Ivánek Jiří

: 3rd International Workshop on Data - Algorithms - Decision Making, (Liblice, CZ, 9.12.2007-11.12.2007)

: CEZ:AV0Z10750506

: 1M0572, GA MŠk, 1ET100750401, GA AV ČR

: multiple participant, decision making, fully probabilistic design

(eng): 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.

(cze): Existuje mnoho axiomatických formulací rozhodování za neurčitosti. Žádná z nich však plně nevyhovuje popisu rozhodování v uzavřené smyčce. Tento příspěvek je pokusem zaplnit tuto mezeru. Formalizuje tzv. plně pravděpodobnostní návrh rozhodovacích strategií a zkoumá souvislosti se standardním bayesovským rozhodováním.

: BB

07.01.2019 - 08:39