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Conference Paper (international conference)

Preference Elicitation in Fully Probabilistic Design of Decision Strategies

Kárný Miroslav, Guy Tatiana Valentine

: Proceedings of the 49th IEEE Conference on Decision and Control, p. 5327-5332

: 49th IEEE Conference on Decision and Control, (Atlanta, US, 14.12.2010-18.12.2010)

: CEZ:AV0Z10750506

: GA102/08/0567, GA ČR

: knowledge elicitation, Bayesian decision making, fullz probabilistic design

: 10.1109/CDC.2010.5717087

: http://library.utia.cas.cz/separaty/2010/AS/karny-preference elicitation in fully probabilistic design of decision strategies.pdf

(eng): Any systematic decision-making design selects a decision strategy that makes the resulting closed-loop behaviour close to the desired one. Fully Probabilistic Design (FPD) describes modelled and desired closed-loop behaviours via their distributions. The designed strategy is a minimiser of Kullback-Leibler divergence of these distributions. FPD: i) unifies modelling and aim-expressing languages; ii) directly describes multiple aims and constraints; iii) simplifies an (inevitable) approximate design as it has an explicit minimiser. The paper enriches the theory of FPD, in particular, it: i) improves its axiomatic basis; ii) quantitatively relates FPD to standard Bayesian decision making showing that the set of FPD tasks is a dense extension of Bayesian problem formulations; iii) opens a way to a systematic data-based preference elicitation, i.e., quantitative expression of decision-making aims.

: BB

07.01.2019 - 08:39