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Bibliografie

Conference Paper (international conference)

Lazy Fully Probabilistic Design: Application Potential

Guy Tatiana Valentine, Fakhimi Derakhshan Siavash, Štěch Jakub

: Multi-Agent Systems and Agreement Technologies, p. 281-291 , Eds: Belardinelli F.

: European Conference on Multi-Agent Systems (EUMAS) 2017 /15./, (Évry, FR, 20171214)

: GA16-09848S, GA ČR

: lazy learning, fully probabilistic design, decision making, linear quadratic Gaussian control

: 10.1007/978-3-030-01713-2_20

: http://library.utia.cas.cz/separaty/2017/AS/guy-0483831.pdf

(eng): The article addresses a lazy learning approach to fully probabilistic decision making when a decision maker (human or arti_cial) uses incomplete knowledge of environment and faces high computational limitations. The resulting lazy Fully Probabilistic Design (FPD) selects a decision strategy that moves a probabilistic description of the closed decision loop to a pre-speci_ed ideal description. The lazy FPD uses currently observed data to _nd past closed-loop similar to the actual ideal model. The optimal decision rule of the closest model is then used in the current step. The e_ectiveness and capability of the proposed approach are manifested through example.

: BC

: 10201

07.01.2019 - 08:39